Merge 485cb85a552c5bd5b6387569da9b1727332e940e into ea2d2a81667239d37615697e8f0056e35bab2db6

Update README.md
Update Documentation (#2768 )
2026-04-29 12:34:03 +08:00 · 2026-04-20 10:05:33 +00:00 · 2026-04-19 21:02:57 +08:00 · 2026-04-18 22:33:55 +08:00 · 2026-04-18 19:01:11 +08:00 · 2026-04-18 17:33:53 +08:00
20 changed files with 1225 additions and 194 deletions
--- a/GPT_SoVITS/AR/data/dataset.py
+++ b/GPT_SoVITS/AR/data/dataset.py
@ -67,8 +67,10 @@ class Text2SemanticDataset(Dataset):
            )
        )  # "%s/3-bert"%exp_dir#bert_dir
        self.path6 = semantic_path  # "%s/6-name2semantic.tsv"%exp_dir#semantic_path
-        assert os.path.exists(self.path2)
-        assert os.path.exists(self.path6)
+        if not os.path.exists(self.path2):
+            raise FileNotFoundError(f"Phoneme data file not found: {self.path2}")
+        if not os.path.exists(self.path6):
+            raise FileNotFoundError(f"Semantic data file not found: {self.path6}")
        self.phoneme_data = {}
        with open(self.path2, "r", encoding="utf8") as f:
            lines = f.read().strip("\n").split("\n")
@ -131,7 +133,7 @@ class Text2SemanticDataset(Dataset):
                phoneme, word2ph, text = self.phoneme_data[item_name]
            except Exception:
                traceback.print_exc()
-                # print(f"{item_name} not in self.phoneme_data !")
+                print(f"Warning: File \"{item_name}\" not in self.phoneme_data! Skipped. ")
                num_not_in += 1
                continue

@ -152,7 +154,7 @@ class Text2SemanticDataset(Dataset):
                phoneme_ids = cleaned_text_to_sequence(phoneme, version)
            except:
                traceback.print_exc()
-                # print(f"{item_name} not in self.phoneme_data !")
+                print(f"Warning: Failed to convert phonemes to sequence for file \"{item_name}\"! Skipped. ")
                num_not_in += 1
                continue
            # if len(phoneme_ids) >400:###########2：改为恒定限制为semantic/2.5就行
@ -228,7 +230,11 @@ class Text2SemanticDataset(Dataset):
            # bert_feature=torch.zeros_like(phoneme_ids,dtype=torch.float32)
            bert_feature = None
        else:
-            assert bert_feature.shape[-1] == len(phoneme_ids)
+            try:
+                assert bert_feature.shape[-1] == len(phoneme_ids)
+            except AssertionError:
+                print(f"AssertionError: The BERT feature dimension ({bert_feature.shape[-1]}) of the file '{item_name}' does not match the length of the phoneme sequence ({len(phoneme_ids)}).")
+                raise
        return {
            "idx": idx,
            "phoneme_ids": phoneme_ids,
--- a/GPT_SoVITS/AR/models/utils.py
+++ b/GPT_SoVITS/AR/models/utils.py
@ -262,7 +262,7 @@ def make_reject_y(y_o, y_lens):
    reject_y = []
    reject_y_lens = []
    for b in range(bs):
-        process_item_idx = torch.randint(0, 1, size=(1,))[0]
+        process_item_idx = torch.randint(0, 2, size=(1,))[0]
        if process_item_idx == 0:
            new_y = repeat_P(y_o[b])
            reject_y.append(new_y)
--- a/GPT_SoVITS/AR/modules/patched_mha_with_cache_onnx.py
+++ b/GPT_SoVITS/AR/modules/patched_mha_with_cache_onnx.py
@ -8,30 +8,30 @@ def multi_head_attention_forward_patched(
    query,
    key,
    value,
-    embed_dim_to_check: int,
-    num_heads: int,
+    embed_dim_to_check,
+    num_heads,
    in_proj_weight,
-    in_proj_bias: Optional[Tensor],
-    bias_k: Optional[Tensor],
-    bias_v: Optional[Tensor],
-    add_zero_attn: bool,
-    dropout_p: float,
-    out_proj_weight: Tensor,
-    out_proj_bias: Optional[Tensor],
-    training: bool = True,
-    key_padding_mask: Optional[Tensor] = None,
-    need_weights: bool = True,
-    attn_mask: Optional[Tensor] = None,
-    use_separate_proj_weight: bool = False,
-    q_proj_weight: Optional[Tensor] = None,
-    k_proj_weight: Optional[Tensor] = None,
-    v_proj_weight: Optional[Tensor] = None,
-    static_k: Optional[Tensor] = None,
-    static_v: Optional[Tensor] = None,
-    average_attn_weights: bool = True,
-    is_causal: bool = False,
+    in_proj_bias,
+    bias_k,
+    bias_v,
+    add_zero_attn,
+    dropout_p,
+    out_proj_weight,
+    out_proj_bias,
+    training=True,
+    key_padding_mask=None,
+    need_weights=True,
+    attn_mask=None,
+    use_separate_proj_weight=False,
+    q_proj_weight=None,
+    k_proj_weight=None,
+    v_proj_weight=None,
+    static_k=None,
+    static_v=None,
+    average_attn_weights=True,
+    is_causal=False,
    cache=None,
-) -> Tuple[Tensor, Optional[Tensor]]:
+):
    # set up shape vars
    _, _, embed_dim = query.shape
    attn_mask = _canonical_mask(
--- a/GPT_SoVITS/TTS_infer_pack/TTS.py
+++ b/GPT_SoVITS/TTS_infer_pack/TTS.py
@ -499,7 +499,7 @@ class TTS:

        if if_lora_v3 == True and os.path.exists(path_sovits) == False:
            info = path_sovits + i18n("SoVITS %s 底模缺失，无法加载相应 LoRA 权重" % model_version)
-            raise FileExistsError(info)
+            raise FileNotFoundError(info)

        # dict_s2 = torch.load(weights_path, map_location=self.configs.device,weights_only=False)
        dict_s2 = load_sovits_new(weights_path)
@ -1578,16 +1578,15 @@ class TTS:
                max_audio = np.abs(audio).max()
                if max_audio > 1:
                    audio /= max_audio
-            audio = (audio * 32768).astype(np.int16)
+                audio = (audio * 32768).astype(np.int16)
+            else:
+                audio = audio.cpu().numpy()
+                audio = (audio * 32768).astype(np.int16)
            t2 = time.perf_counter()
            print(f"超采样用时：{t2 - t1:.3f}s")
        else:
-            # audio = audio.float() * 32768
-            # audio = audio.to(dtype=torch.int16).clamp(-32768, 32767).cpu().numpy()
-
            audio = audio.cpu().numpy()
-
-        audio = (audio * 32768).astype(np.int16)
+            audio = (audio * 32768).astype(np.int16)


        # try:
@ -1768,7 +1767,10 @@ class TTS:
            pos += chunk_len * upsample_rate

        audio = self.sola_algorithm(audio_fragments, overlapped_len * upsample_rate)
-        audio = audio[overlapped_len * upsample_rate : -padding_len * upsample_rate]
+        if padding_len > 0:
+            audio = audio[overlapped_len * upsample_rate : -padding_len * upsample_rate]
+        else:
+            audio = audio[overlapped_len * upsample_rate :]

        audio_fragments = []
        for feat_len in feat_lens:
--- a/GPT_SoVITS/TTS_infer_pack/text_segmentation_method.py
+++ b/GPT_SoVITS/TTS_infer_pack/text_segmentation_method.py
@ -92,7 +92,7 @@ def cut0(inp):
    if not set(inp).issubset(punctuation):
        return inp
    else:
-        return "/n"
+        return "\n"


 # 凑四句一切
--- a/GPT_SoVITS/inference_cli.py
+++ b/GPT_SoVITS/inference_cli.py
@ -7,79 +7,163 @@ from GPT_SoVITS.inference_webui import change_gpt_weights, change_sovits_weights

 i18n = I18nAuto()

+LANGUAGE_CHOICES = ["中文", "英文", "日文", "韩文", "粤语"]
+MIXED_LANGUAGE_CHOICES = ["中英混合", "日英混合", "粤英混合", "韩英混合", "多语种混合"]

-def synthesize(
-    GPT_model_path,
-    SoVITS_model_path,
-    ref_audio_path,
-    ref_text_path,
-    ref_language,
-    target_text_path,
-    target_language,
-    output_path,
-):
-    # Read reference text
-    with open(ref_text_path, "r", encoding="utf-8") as file:
-        ref_text = file.read()
+SLICE_METHOD_CHOICES = ["凑四句一切", "凑50字一切", "按标点符号切", "按中文句号。切", "按英文句号.切"]

-    # Read target text
-    with open(target_text_path, "r", encoding="utf-8") as file:
-        target_text = file.read()
+def synthesize(args: argparse.Namespace):

    # Change model weights
-    change_gpt_weights(gpt_path=GPT_model_path)
-    change_sovits_weights(sovits_path=SoVITS_model_path)
+    change_gpt_weights(gpt_path=args.gpt_path)
+    change_sovits_weights(sovits_path=args.sovits_path)
+
+    params = {
+        "ref_wav_path": args.ref_audio,
+        "prompt_text": args.ref_text,
+        "prompt_language": i18n(args.ref_language),
+        "text": args.target_text,
+        "text_language": i18n(args.target_language),
+    }
+
+    # region - optional params
+    if args.slicer: params["how_to_cut"] = i18n(args.slicer)
+    if args.top_k: params["top_k"] = args.top_k
+    if args.top_p: params["top_p"] = args.top_p
+    if args.temperature: params["temperature"] = args.temperature
+    if args.ref_free: params["ref_free"] = args.ref_free
+    if args.speed: params["speed"] = args.speed
+    if args.if_freeze: params["if_freeze"] = args.if_freeze
+    if args.inp_refs: params["inp_refs"] = args.inp_refs
+    if args.sample_steps: params["sample_steps"] = args.sample_steps
+    if args.if_sr: params["if_sr"] = args.if_sr
+    if args.pause_second: params["pause_second"] = args.pause_second
+    # endregion - optional params

    # Synthesize audio
-    synthesis_result = get_tts_wav(
-        ref_wav_path=ref_audio_path,
-        prompt_text=ref_text,
-        prompt_language=i18n(ref_language),
-        text=target_text,
-        text_language=i18n(target_language),
-        top_p=1,
-        temperature=1,
-    )
+    synthesis_result = get_tts_wav(**params)

    result_list = list(synthesis_result)

    if result_list:
+        os.makedirs(args.output_path, exist_ok=True) # Create output directory if it doesn't exist
+        if args.output_path.endswith(".wav"):
+            output_wav_path = args.output_path
+        else:
+            output_wav_path = os.path.join(args.output_path, "output.wav")
        last_sampling_rate, last_audio_data = result_list[-1]
-        output_wav_path = os.path.join(output_path, "output.wav")
        sf.write(output_wav_path, last_audio_data, last_sampling_rate)
        print(f"Audio saved to {output_wav_path}")


-def main():
+def build_parser():
    parser = argparse.ArgumentParser(description="GPT-SoVITS Command Line Tool")
-    parser.add_argument("--gpt_model", required=True, help="Path to the GPT model file")
-    parser.add_argument("--sovits_model", required=True, help="Path to the SoVITS model file")
+
+    # reference settings
    parser.add_argument("--ref_audio", required=True, help="Path to the reference audio file")
-    parser.add_argument("--ref_text", required=True, help="Path to the reference text file")
-    parser.add_argument(
-        "--ref_language", required=True, choices=["中文", "英文", "日文"], help="Language of the reference audio"
-    )
-    parser.add_argument("--target_text", required=True, help="Path to the target text file")
-    parser.add_argument(
-        "--target_language",
-        required=True,
-        choices=["中文", "英文", "日文", "中英混合", "日英混合", "多语种混合"],
-        help="Language of the target text",
-    )
+    parser.add_argument("--ref_text", required=True, help="Transcript of the reference audio")
+    parser.add_argument("--ref_language", required=True,
+                       choices=LANGUAGE_CHOICES, help="Language of the reference audio")
+
+    # output settings
+    parser.add_argument("--target_text", required=True, help="Text to be synthesized")
+    parser.add_argument("--target_language", required=True,
+                       choices=LANGUAGE_CHOICES+MIXED_LANGUAGE_CHOICES,
+                       help="Language of the target text")
+    parser.add_argument("--slicer", required=False,
+                       choices=SLICE_METHOD_CHOICES, help="Slicer method")
    parser.add_argument("--output_path", required=True, help="Path to the output directory")

+    # region - inference settings
+    parser.add_argument("--top_k", required=False, type=int, help="Top-k value")
+    parser.add_argument("--top_p", required=False, type=float, help="Top-p value")
+    parser.add_argument("--temperature", required=False, type=float, help="Temperature value")
+    parser.add_argument("--ref_free", required=False, type=bool, help="Reference free value")
+    parser.add_argument("--speed", required=False, type=float, help="Speed value")
+    parser.add_argument("--if_freeze", required=False, type=bool, help="If freeze value")
+    parser.add_argument("--inp_refs", required=False, type=str, help="Input references")
+    parser.add_argument("--sample_steps", required=False, type=int, help="Sample steps value")
+    parser.add_argument("--if_sr", required=False, type=bool, help="If super resolution value")
+    parser.add_argument("--pause_second", required=False, type=float, help="Pause second value")
+    # endregion - inference settings
+
+    # region - model selection
+    sub = parser.add_subparsers(dest="mode", required=True)
+
+    # Mode 1: provide model paths directly
+    p_paths = sub.add_parser("paths", help="Use explicit model file paths")
+    p_paths.add_argument("--gpt_path", required=True, help="Path to the GPT model file")
+    p_paths.add_argument("--sovits_path", required=True, help="Path to the SoVITS model file")
+
+    # Mode 2: select by experiment/version
+    p_sel = sub.add_parser("select", help="Select models by experiment/version")
+    p_sel.add_argument("--exp_name", required=True, help="Experiment name")
+    available_gpt_versions = ["v1", "v2", "v2Pro", "v2ProPlus", "v3", "v4"]
+    p_sel.add_argument("--gpt_version", required=True, choices=available_gpt_versions, help="Version of the GPT model")
+    available_sovits_versions = ["v1", "v2", "v2Pro", "v2ProPlus", "v3", "v4"]
+    p_sel.add_argument("--sovits_version", required=True, choices=available_sovits_versions, help="Version of the SoVITS model")
+    p_sel.add_argument("--gpt_epoch", type=int, help="Epoch of the GPT model")
+    p_sel.add_argument("--sovits_epoch", type=int, help="Epoch of the SoVITS model")
+    # endregion - model selection
+
+    return parser
+
+
+def get_model_path(args)->argparse.Namespace:
+    """
+    Get the model path from exp_name, version and epoch
+
+    Args:
+        args: argparse.Namespace
+
+    Returns:
+        args: argparse.Namespace
+    """
+    exist_gpt_path = []
+    exist_sovits_path = []
+
+    def _get_model_dir(model_type, version):
+        if version == "v1":
+            return f"{model_type}_weights"
+        else:
+            return f"{model_type}_weights_{version}"
+
+    # get all the model paths with the same exp_name
+    for files in os.listdir(_get_model_dir("GPT", args.gpt_version)):
+        if args.exp_name in files and files.endswith(".ckpt"):
+            exist_gpt_path.append(os.path.join(_get_model_dir("GPT", args.gpt_version), files))
+    for files in os.listdir(_get_model_dir("SoVITS", args.sovits_version)):
+        if args.exp_name in files and files.endswith(".pth"):
+            exist_sovits_path.append(os.path.join(_get_model_dir("SoVITS", args.sovits_version), files))
+
+    # get the largest epoch if not specified
+    if args.gpt_epoch:
+        args.gpt_path = [i for i in exist_gpt_path if f"e{args.gpt_epoch}" in i]
+    else:
+        args.gpt_path = sorted(exist_gpt_path)[-1]
+    if args.sovits_epoch:
+        args.sovits_path = [i for i in exist_sovits_path if f"e{args.sovits_epoch}" in i]
+    else:
+        args.sovits_path = sorted(exist_sovits_path)[-1]
+
+    if not args.gpt_path or not args.sovits_path:
+        raise ValueError("No model found")
+    
+    return args
+
+
+def main():
+    parser = build_parser()
    args = parser.parse_args()

-    synthesize(
-        args.gpt_model,
-        args.sovits_model,
-        args.ref_audio,
-        args.ref_text,
-        args.ref_language,
-        args.target_text,
-        args.target_language,
-        args.output_path,
-    )
+    print(args)
+    if args.mode == "select":
+        args = get_model_path(args)
+    
+    args.target_text = args.target_text.replace("'", "").replace('"', "")
+
+
+    synthesize(args)


 if __name__ == "__main__":
--- a/GPT_SoVITS/inference_webui.py
+++ b/GPT_SoVITS/inference_webui.py
@ -180,6 +180,8 @@ def get_bert_feature(text, word2ph):
    for i in range(len(word2ph)):
        repeat_feature = res[i].repeat(word2ph[i], 1)
        phone_level_feature.append(repeat_feature)
+    if len(phone_level_feature) == 0:
+        return torch.empty((res.shape[1], 0), dtype=res.dtype, device=res.device)
    phone_level_feature = torch.cat(phone_level_feature, dim=0)
    return phone_level_feature.T

--- a/GPT_SoVITS/module/distrib.py
+++ b/GPT_SoVITS/module/distrib.py
@ -87,7 +87,7 @@ def sync_buffer(buffers, average=True):
    for buffer, handle in handles:
        handle.wait()
        if average:
-            buffer.data /= world_size
+            buffer.data /= world_size()


 def sync_grad(params):
--- a/GPT_SoVITS/s2_train_v3_lora.py
+++ b/GPT_SoVITS/s2_train_v3_lora.py
@ -55,6 +55,10 @@ def main():
        n_gpus = torch.cuda.device_count()
    else:
        n_gpus = 1
+    if n_gpus <= 1:
+        run(0, n_gpus, hps)
+        return
+
    os.environ["MASTER_ADDR"] = "localhost"
    os.environ["MASTER_PORT"] = str(randint(20000, 55555))

@ -77,12 +81,14 @@ def run(rank, n_gpus, hps):
        writer = SummaryWriter(log_dir=hps.s2_ckpt_dir)
        writer_eval = SummaryWriter(log_dir=os.path.join(hps.s2_ckpt_dir, "eval"))

-    dist.init_process_group(
-        backend="gloo" if os.name == "nt" or not torch.cuda.is_available() else "nccl",
-        init_method="env://?use_libuv=False",
-        world_size=n_gpus,
-        rank=rank,
-    )
+    use_ddp = n_gpus > 1
+    if use_ddp:
+        dist.init_process_group(
+            backend="gloo" if os.name == "nt" or not torch.cuda.is_available() else "nccl",
+            init_method="env://?use_libuv=False",
+            world_size=n_gpus,
+            rank=rank,
+        )
    torch.manual_seed(hps.train.seed)
    if torch.cuda.is_available():
        torch.cuda.set_device(rank)
@ -118,15 +124,20 @@ def run(rank, n_gpus, hps):
        shuffle=True,
    )
    collate_fn = TextAudioSpeakerCollate()
-    train_loader = DataLoader(
-        train_dataset,
-        num_workers=5,
+    worker_count = 0 if os.name == "nt" and n_gpus <= 1 else min(2 if os.name == "nt" else 5, os.cpu_count() or 1)
+    loader_kwargs = dict(
+        num_workers=worker_count,
        shuffle=False,
-        pin_memory=True,
+        pin_memory=torch.cuda.is_available(),
        collate_fn=collate_fn,
        batch_sampler=train_sampler,
-        persistent_workers=True,
-        prefetch_factor=3,
+    )
+    if worker_count > 0:
+        loader_kwargs["persistent_workers"] = True
+        loader_kwargs["prefetch_factor"] = 2 if os.name == "nt" else 3
+    train_loader = DataLoader(
+        train_dataset,
+        **loader_kwargs,
    )
    save_root = "%s/logs_s2_%s_lora_%s" % (hps.data.exp_dir, hps.model.version, hps.train.lora_rank)
    os.makedirs(save_root, exist_ok=True)
@ -156,7 +167,9 @@ def run(rank, n_gpus, hps):

    def model2cuda(net_g, rank):
        if torch.cuda.is_available():
-            net_g = DDP(net_g.cuda(rank), device_ids=[rank], find_unused_parameters=True)
+            net_g = net_g.cuda(rank)
+            if use_ddp:
+                net_g = DDP(net_g, device_ids=[rank], find_unused_parameters=True)
        else:
            net_g = net_g.to(device)
        return net_g
@ -242,6 +255,8 @@ def run(rank, n_gpus, hps):
                None,
            )
        scheduler_g.step()
+    if use_ddp and dist.is_initialized():
+        dist.destroy_process_group()
    print("training done")


--- a/GPT_SoVITS/text/chinese2.py
+++ b/GPT_SoVITS/text/chinese2.py
@ -180,10 +180,15 @@ def _merge_erhua(initials: list[str], finals: list[str], word: str, pos: str) ->
 def _g2p(segments):
    phones_list = []
    word2ph = []
-    for seg in segments:
+    g2pw_batch_results = []
+    g2pw_batch_cursor = 0
+    processed_segments = [re.sub("[a-zA-Z]+", "", seg) for seg in segments]
+    if is_g2pw:
+        batch_inputs = [seg for seg in processed_segments if seg]
+        g2pw_batch_results = g2pw._g2pw(batch_inputs) if batch_inputs else []
+
+    for seg in processed_segments:
        pinyins = []
-        # Replace all English words in the sentence
-        seg = re.sub("[a-zA-Z]+", "", seg)
        seg_cut = psg.lcut(seg)
        seg_cut = tone_modifier.pre_merge_for_modify(seg_cut)
        initials = []
@ -204,8 +209,10 @@ def _g2p(segments):
            finals = sum(finals, [])
            print("pypinyin结果", initials, finals)
        else:
-            # g2pw采用整句推理
-            pinyins = g2pw.lazy_pinyin(seg, neutral_tone_with_five=True, style=Style.TONE3)
+            # g2pw采用整句推理（批量推理，逐句取结果）
+            if seg:
+                pinyins = g2pw_batch_results[g2pw_batch_cursor]
+                g2pw_batch_cursor += 1

            pre_word_length = 0
            for word, pos in seg_cut:
--- a/GPT_SoVITS/text/g2pw/dataset.py
+++ b/GPT_SoVITS/text/g2pw/dataset.py
@ -18,6 +18,7 @@ Credits

 from typing import Dict
 from typing import List
+from typing import Optional
 from typing import Tuple

 import numpy as np
@ -37,6 +38,8 @@ def prepare_onnx_input(
    use_mask: bool = False,
    window_size: int = None,
    max_len: int = 512,
+    char2id: Optional[Dict[str, int]] = None,
+    char_phoneme_masks: Optional[Dict[str, List[int]]] = None,
 ) -> Dict[str, np.array]:
    if window_size is not None:
        truncated_texts, truncated_query_ids = _truncate_texts(
@ -48,33 +51,88 @@ def prepare_onnx_input(
    phoneme_masks = []
    char_ids = []
    position_ids = []
+    tokenized_cache = {}
+
+    if char2id is None:
+        char2id = {char: idx for idx, char in enumerate(chars)}
+    if use_mask:
+        if char_phoneme_masks is None:
+            char_phoneme_masks = {
+                char: [1 if i in char2phonemes[char] else 0 for i in range(len(labels))]
+                for char in char2phonemes
+            }
+    else:
+        full_phoneme_mask = [1] * len(labels)

    for idx in range(len(texts)):
        text = (truncated_texts if window_size else texts)[idx].lower()
        query_id = (truncated_query_ids if window_size else query_ids)[idx]

-        try:
-            tokens, text2token, token2text = tokenize_and_map(tokenizer=tokenizer, text=text)
-        except Exception:
-            print(f'warning: text "{text}" is invalid')
-            return {}
+        cached = tokenized_cache.get(text)
+        if cached is None:
+            try:
+                tokens, text2token, token2text = tokenize_and_map(tokenizer=tokenizer, text=text)
+            except Exception:
+                print(f'warning: text "{text}" is invalid')
+                return {}

-        text, query_id, tokens, text2token, token2text = _truncate(
-            max_len=max_len, text=text, query_id=query_id, tokens=tokens, text2token=text2token, token2text=token2text
-        )
+            if len(tokens) <= max_len - 2:
+                processed_tokens = ["[CLS]"] + tokens + ["[SEP]"]
+                shared_input_id = list(np.array(tokenizer.convert_tokens_to_ids(processed_tokens)))
+                shared_token_type_id = list(np.zeros((len(processed_tokens),), dtype=int))
+                shared_attention_mask = list(np.ones((len(processed_tokens),), dtype=int))
+                cached = {
+                    "is_short": True,
+                    "tokens": tokens,
+                    "text2token": text2token,
+                    "token2text": token2text,
+                    "input_id": shared_input_id,
+                    "token_type_id": shared_token_type_id,
+                    "attention_mask": shared_attention_mask,
+                }
+            else:
+                cached = {
+                    "is_short": False,
+                    "tokens": tokens,
+                    "text2token": text2token,
+                    "token2text": token2text,
+                }
+            tokenized_cache[text] = cached

-        processed_tokens = ["[CLS]"] + tokens + ["[SEP]"]
+        if cached["is_short"]:
+            text_for_query = text
+            query_id_for_query = query_id
+            text2token_for_query = cached["text2token"]
+            input_id = cached["input_id"]
+            token_type_id = cached["token_type_id"]
+            attention_mask = cached["attention_mask"]
+        else:
+            (
+                text_for_query,
+                query_id_for_query,
+                tokens_for_query,
+                text2token_for_query,
+                _token2text_for_query,
+            ) = _truncate(
+                max_len=max_len,
+                text=text,
+                query_id=query_id,
+                tokens=cached["tokens"],
+                text2token=cached["text2token"],
+                token2text=cached["token2text"],
+            )
+            processed_tokens = ["[CLS]"] + tokens_for_query + ["[SEP]"]
+            input_id = list(np.array(tokenizer.convert_tokens_to_ids(processed_tokens)))
+            token_type_id = list(np.zeros((len(processed_tokens),), dtype=int))
+            attention_mask = list(np.ones((len(processed_tokens),), dtype=int))

-        input_id = list(np.array(tokenizer.convert_tokens_to_ids(processed_tokens)))
-        token_type_id = list(np.zeros((len(processed_tokens),), dtype=int))
-        attention_mask = list(np.ones((len(processed_tokens),), dtype=int))
-
-        query_char = text[query_id]
-        phoneme_mask = (
-            [1 if i in char2phonemes[query_char] else 0 for i in range(len(labels))] if use_mask else [1] * len(labels)
-        )
-        char_id = chars.index(query_char)
-        position_id = text2token[query_id] + 1  # [CLS] token locate at first place
+        query_char = text_for_query[query_id_for_query]
+        if use_mask:
+            phoneme_mask = char_phoneme_masks[query_char]
+        else:
+            phoneme_mask = full_phoneme_mask
+        char_id = char2id[query_char]
+        position_id = text2token_for_query[query_id_for_query] + 1  # [CLS] token locate at first place

        input_ids.append(input_id)
        token_type_ids.append(token_type_id)
@ -83,10 +141,15 @@ def prepare_onnx_input(
        char_ids.append(char_id)
        position_ids.append(position_id)

+    max_token_length = max(len(seq) for seq in input_ids)
+
+    def _pad_sequences(sequences, pad_value=0):
+        return [seq + [pad_value] * (max_token_length - len(seq)) for seq in sequences]
+
    outputs = {
-        "input_ids": np.array(input_ids).astype(np.int64),
-        "token_type_ids": np.array(token_type_ids).astype(np.int64),
-        "attention_masks": np.array(attention_masks).astype(np.int64),
+        "input_ids": np.array(_pad_sequences(input_ids, pad_value=0)).astype(np.int64),
+        "token_type_ids": np.array(_pad_sequences(token_type_ids, pad_value=0)).astype(np.int64),
+        "attention_masks": np.array(_pad_sequences(attention_masks, pad_value=0)).astype(np.int64),
        "phoneme_masks": np.array(phoneme_masks).astype(np.float32),
        "char_ids": np.array(char_ids).astype(np.int64),
        "position_ids": np.array(position_ids).astype(np.int64),
--- a/GPT_SoVITS/text/g2pw/onnx_api.py
+++ b/GPT_SoVITS/text/g2pw/onnx_api.py
@ -10,7 +10,6 @@ from typing import Any, Dict, List, Tuple
 import numpy as np
 import onnxruntime
 import requests
-import torch
 from opencc import OpenCC
 from pypinyin import Style, pinyin
 from transformers.models.auto.tokenization_auto import AutoTokenizer
@ -22,9 +21,8 @@ from .utils import load_config
 onnxruntime.set_default_logger_severity(3)
 try:
    onnxruntime.preload_dlls()
-except:
+except Exception:
    pass
-    # traceback.print_exc()
 warnings.filterwarnings("ignore")

 model_version = "1.1"
@ -55,6 +53,24 @@ def predict(session, onnx_input: Dict[str, Any], labels: List[str]) -> Tuple[Lis
    return all_preds, all_confidences


+def _load_json_from_candidates(filename: str, candidate_dirs: List[str]) -> Dict[str, Any]:
+    for candidate_dir in candidate_dirs:
+        if not candidate_dir:
+            continue
+        json_path = os.path.join(candidate_dir, filename)
+        if os.path.exists(json_path):
+            with open(json_path, "r", encoding="utf-8") as fr:
+                return json.load(fr)
+    raise FileNotFoundError(f"Cannot locate {filename} in candidate dirs: {candidate_dirs}")
+
+
+def _find_first_existing_file(*paths: str) -> str:
+    for path in paths:
+        if path and os.path.exists(path):
+            return path
+    raise FileNotFoundError(f"Files not found: {paths}")
+
+
 def download_and_decompress(model_dir: str = "G2PWModel/"):
    if not os.path.exists(model_dir):
        parent_directory = os.path.dirname(model_dir)
@ -62,7 +78,7 @@ def download_and_decompress(model_dir: str = "G2PWModel/"):
        extract_dir = os.path.join(parent_directory, "G2PWModel_1.1")
        extract_dir_new = os.path.join(parent_directory, "G2PWModel")
        print("Downloading g2pw model...")
-        modelscope_url = "https://www.modelscope.cn/models/kamiorinn/g2pw/resolve/master/G2PWModel_1.1.zip"  # "https://paddlespeech.cdn.bcebos.com/Parakeet/released_models/g2p/G2PWModel_1.1.zip"
+        modelscope_url = "https://www.modelscope.cn/models/kamiorinn/g2pw/resolve/master/G2PWModel_1.1.zip"
        with requests.get(modelscope_url, stream=True) as r:
            r.raise_for_status()
            with open(zip_dir, "wb") as f:
@ -79,7 +95,7 @@ def download_and_decompress(model_dir: str = "G2PWModel/"):
    return model_dir


-class G2PWOnnxConverter:
+class _G2PWBaseOnnxConverter:
    def __init__(
        self,
        model_dir: str = "G2PWModel/",
@ -87,33 +103,16 @@ class G2PWOnnxConverter:
        model_source: str = None,
        enable_non_tradional_chinese: bool = False,
    ):
-        uncompress_path = download_and_decompress(model_dir)
-
-        sess_options = onnxruntime.SessionOptions()
-        sess_options.graph_optimization_level = onnxruntime.GraphOptimizationLevel.ORT_ENABLE_ALL
-        sess_options.execution_mode = onnxruntime.ExecutionMode.ORT_SEQUENTIAL
-        sess_options.intra_op_num_threads = 2 if torch.cuda.is_available() else 0
-        if "CUDAExecutionProvider" in onnxruntime.get_available_providers():
-            self.session_g2pW = onnxruntime.InferenceSession(
-                os.path.join(uncompress_path, "g2pW.onnx"),
-                sess_options=sess_options,
-                providers=["CUDAExecutionProvider", "CPUExecutionProvider"],
-            )
-        else:
-            self.session_g2pW = onnxruntime.InferenceSession(
-                os.path.join(uncompress_path, "g2pW.onnx"),
-                sess_options=sess_options,
-                providers=["CPUExecutionProvider"],
-            )
-        self.config = load_config(config_path=os.path.join(uncompress_path, "config.py"), use_default=True)
+        self.model_dir = download_and_decompress(model_dir)
+        self.config = load_config(config_path=os.path.join(self.model_dir, "config.py"), use_default=True)

        self.model_source = model_source if model_source else self.config.model_source
        self.enable_opencc = enable_non_tradional_chinese
-
        self.tokenizer = AutoTokenizer.from_pretrained(self.model_source)

-        polyphonic_chars_path = os.path.join(uncompress_path, "POLYPHONIC_CHARS.txt")
-        monophonic_chars_path = os.path.join(uncompress_path, "MONOPHONIC_CHARS.txt")
+        polyphonic_chars_path = os.path.join(self.model_dir, "POLYPHONIC_CHARS.txt")
+        monophonic_chars_path = os.path.join(self.model_dir, "MONOPHONIC_CHARS.txt")
+
        self.polyphonic_chars = [
            line.split("\t") for line in open(polyphonic_chars_path, encoding="utf-8").read().strip().split("\n")
        ]
@ -149,31 +148,47 @@ class G2PWOnnxConverter:
        )

        self.chars = sorted(list(self.char2phonemes.keys()))
+        self.char2id = {char: idx for idx, char in enumerate(self.chars)}
+        self.char_phoneme_masks = (
+            {
+                char: [1 if i in self.char2phonemes[char] else 0 for i in range(len(self.labels))]
+                for char in self.char2phonemes
+            }
+            if self.config.use_mask
+            else None
+        )

        self.polyphonic_chars_new = set(self.chars)
        for char in self.non_polyphonic:
-            if char in self.polyphonic_chars_new:
-                self.polyphonic_chars_new.remove(char)
+            self.polyphonic_chars_new.discard(char)

        self.monophonic_chars_dict = {char: phoneme for char, phoneme in self.monophonic_chars}
        for char in self.non_monophonic:
-            if char in self.monophonic_chars_dict:
-                self.monophonic_chars_dict.pop(char)
+            self.monophonic_chars_dict.pop(char, None)

-        self.pos_tags = ["UNK", "A", "C", "D", "I", "N", "P", "T", "V", "DE", "SHI"]
+        default_asset_dir = os.path.normpath(os.path.join(os.path.dirname(__file__), "..", "G2PWModel"))
+        candidate_asset_dirs = [self.model_dir, default_asset_dir]
+        self.bopomofo_convert_dict = _load_json_from_candidates(
+            "bopomofo_to_pinyin_wo_tune_dict.json", candidate_asset_dirs
+        )
+        self.char_bopomofo_dict = _load_json_from_candidates("char_bopomofo_dict.json", candidate_asset_dirs)

-        with open(os.path.join(uncompress_path, "bopomofo_to_pinyin_wo_tune_dict.json"), "r", encoding="utf-8") as fr:
-            self.bopomofo_convert_dict = json.load(fr)
        self.style_convert_func = {
            "bopomofo": lambda x: x,
            "pinyin": self._convert_bopomofo_to_pinyin,
        }[style]

-        with open(os.path.join(uncompress_path, "char_bopomofo_dict.json"), "r", encoding="utf-8") as fr:
-            self.char_bopomofo_dict = json.load(fr)
-
        if self.enable_opencc:
            self.cc = OpenCC("s2tw")
+        self.enable_sentence_dedup = os.getenv("g2pw_sentence_dedup", "true").strip().lower() in {
+            "1",
+            "true",
+            "yes",
+            "y",
+            "on",
+        }
+        # 聚焦到多音字附近上下文，默认左右各16字；设为0表示关闭裁剪（整句）。
+        self.polyphonic_context_chars = max(0, int(os.getenv("g2pw_polyphonic_context_chars", "16")))

    def _convert_bopomofo_to_pinyin(self, bopomofo: str) -> str:
        tone = bopomofo[-1]
@ -181,9 +196,8 @@ class G2PWOnnxConverter:
        component = self.bopomofo_convert_dict.get(bopomofo[:-1])
        if component:
            return component + tone
-        else:
-            print(f'Warning: "{bopomofo}" cannot convert to pinyin')
-            return None
+        print(f'Warning: "{bopomofo}" cannot convert to pinyin')
+        return None

    def __call__(self, sentences: List[str]) -> List[List[str]]:
        if isinstance(sentences, str):
@ -197,51 +211,147 @@ class G2PWOnnxConverter:
                translated_sentences.append(translated_sent)
            sentences = translated_sentences

-        texts, query_ids, sent_ids, partial_results = self._prepare_data(sentences=sentences)
+        texts, model_query_ids, result_query_ids, sent_ids, partial_results = self._prepare_data(sentences=sentences)
        if len(texts) == 0:
-            # sentences no polyphonic words
            return partial_results

-        onnx_input = prepare_onnx_input(
+        model_input = prepare_onnx_input(
            tokenizer=self.tokenizer,
            labels=self.labels,
            char2phonemes=self.char2phonemes,
            chars=self.chars,
            texts=texts,
-            query_ids=query_ids,
+            query_ids=model_query_ids,
            use_mask=self.config.use_mask,
            window_size=None,
+            char2id=self.char2id,
+            char_phoneme_masks=self.char_phoneme_masks,
        )

-        preds, confidences = predict(session=self.session_g2pW, onnx_input=onnx_input, labels=self.labels)
+        if not model_input:
+            return partial_results
+
+        if self.enable_sentence_dedup:
+            preds, _confidences = self._predict_with_sentence_dedup(model_input=model_input, texts=texts)
+        else:
+            preds, _confidences = self._predict(model_input=model_input)
+
        if self.config.use_char_phoneme:
            preds = [pred.split(" ")[1] for pred in preds]

        results = partial_results
-        for sent_id, query_id, pred in zip(sent_ids, query_ids, preds):
+        for sent_id, query_id, pred in zip(sent_ids, result_query_ids, preds):
            results[sent_id][query_id] = self.style_convert_func(pred)

        return results

-    def _prepare_data(self, sentences: List[str]) -> Tuple[List[str], List[int], List[int], List[List[str]]]:
-        texts, query_ids, sent_ids, partial_results = [], [], [], []
+    def _prepare_data(
+        self, sentences: List[str]
+    ) -> Tuple[List[str], List[int], List[int], List[int], List[List[str]]]:
+        texts, model_query_ids, result_query_ids, sent_ids, partial_results = [], [], [], [], []
        for sent_id, sent in enumerate(sentences):
-            # pypinyin works well for Simplified Chinese than Traditional Chinese
            sent_s = tranditional_to_simplified(sent)
            pypinyin_result = pinyin(sent_s, neutral_tone_with_five=True, style=Style.TONE3)
            partial_result = [None] * len(sent)
+            polyphonic_indices: List[int] = []
            for i, char in enumerate(sent):
                if char in self.polyphonic_chars_new:
-                    texts.append(sent)
-                    query_ids.append(i)
-                    sent_ids.append(sent_id)
+                    polyphonic_indices.append(i)
                elif char in self.monophonic_chars_dict:
                    partial_result[i] = self.style_convert_func(self.monophonic_chars_dict[char])
                elif char in self.char_bopomofo_dict:
                    partial_result[i] = pypinyin_result[i][0]
-                    # partial_result[i] =  self.style_convert_func(self.char_bopomofo_dict[char][0])
                else:
                    partial_result[i] = pypinyin_result[i][0]

+            if polyphonic_indices:
+                if self.polyphonic_context_chars > 0:
+                    left = max(0, polyphonic_indices[0] - self.polyphonic_context_chars)
+                    right = min(len(sent), polyphonic_indices[-1] + self.polyphonic_context_chars + 1)
+                    sent_for_predict = sent[left:right]
+                    query_offset = left
+                else:
+                    sent_for_predict = sent
+                    query_offset = 0
+
+                for index in polyphonic_indices:
+                    texts.append(sent_for_predict)
+                    model_query_ids.append(index - query_offset)
+                    result_query_ids.append(index)
+                    sent_ids.append(sent_id)
+
            partial_results.append(partial_result)
-        return texts, query_ids, sent_ids, partial_results
+        return texts, model_query_ids, result_query_ids, sent_ids, partial_results
+
+    def _predict(self, model_input: Dict[str, Any]) -> Tuple[List[str], List[float]]:
+        raise NotImplementedError
+
+    def _predict_with_sentence_dedup(
+        self, model_input: Dict[str, Any], texts: List[str]
+    ) -> Tuple[List[str], List[float]]:
+        if len(texts) <= 1:
+            return self._predict(model_input=model_input)
+
+        grouped_indices: Dict[str, List[int]] = {}
+        for idx, text in enumerate(texts):
+            grouped_indices.setdefault(text, []).append(idx)
+
+        if all(len(indices) == 1 for indices in grouped_indices.values()):
+            return self._predict(model_input=model_input)
+
+        preds: List[str] = [""] * len(texts)
+        confidences: List[float] = [0.0] * len(texts)
+        for indices in grouped_indices.values():
+            group_input = {name: value[indices] for name, value in model_input.items()}
+            if len(indices) > 1:
+                for name in ("input_ids", "token_type_ids", "attention_masks"):
+                    group_input[name] = group_input[name][:1]
+
+            group_preds, group_confidences = self._predict(model_input=group_input)
+            for output_idx, pred, confidence in zip(indices, group_preds, group_confidences):
+                preds[output_idx] = pred
+                confidences[output_idx] = confidence
+
+        return preds, confidences
+
+
+class G2PWOnnxConverter(_G2PWBaseOnnxConverter):
+    def __init__(
+        self,
+        model_dir: str = "G2PWModel/",
+        style: str = "bopomofo",
+        model_source: str = None,
+        enable_non_tradional_chinese: bool = False,
+    ):
+        super().__init__(
+            model_dir=model_dir,
+            style=style,
+            model_source=model_source,
+            enable_non_tradional_chinese=enable_non_tradional_chinese,
+        )
+
+        sess_options = onnxruntime.SessionOptions()
+        sess_options.graph_optimization_level = onnxruntime.GraphOptimizationLevel.ORT_ENABLE_ALL
+        sess_options.execution_mode = onnxruntime.ExecutionMode.ORT_SEQUENTIAL
+        sess_options.intra_op_num_threads = 2
+
+        onnx_path = _find_first_existing_file(
+            os.path.join(self.model_dir, "g2pW.onnx"),
+            os.path.join(self.model_dir, "g2pw.onnx"),
+        )
+
+        if "CUDAExecutionProvider" in onnxruntime.get_available_providers():
+            self.session_g2pw = onnxruntime.InferenceSession(
+                onnx_path,
+                sess_options=sess_options,
+                providers=["CUDAExecutionProvider", "CPUExecutionProvider"],
+            )
+        else:
+            self.session_g2pw = onnxruntime.InferenceSession(
+                onnx_path,
+                sess_options=sess_options,
+                providers=["CPUExecutionProvider"],
+            )
+
+    def _predict(self, model_input: Dict[str, Any]) -> Tuple[List[str], List[float]]:
+        return predict(session=self.session_g2pw, onnx_input=model_input, labels=self.labels)
--- a/README.md
+++ b/README.md
@ -48,6 +48,8 @@ https://github.com/RVC-Boss/GPT-SoVITS/assets/129054828/05bee1fa-bdd8-4d85-9350-

 请不要尬黑GPT-SoVITS推理速度慢，谢谢！

+CPU-Optimized Inference Version：https://github.com/baicai-1145/GPT-SoVITS-CPUFast
+
 **User guide: [简体中文](https://www.yuque.com/baicaigongchang1145haoyuangong/ib3g1e) | [English](https://rentry.co/GPT-SoVITS-guide#/)**

 ## Installation
--- a/docs/cn/Changelog_CN.md
+++ b/docs/cn/Changelog_CN.md
@ -594,11 +594,11 @@
  - 内容: 修复实验名结尾出现空格在win中路径不正确的问题
  - 类型: 修复
  - 提交: RVC-Boss
- 2025.06.10 [Commit#746cb536](https://github.com/RVC-Boss/GPT-SoVITS/commit/746cb536c68b1fe6ce3ca7e882235375b8a8dd89)
+- 2025.06.10 [PR#2449](https://github.com/RVC-Boss/GPT-SoVITS/pull/2449)
  - 内容: 语种分割优化
  - 类型: 优化
  - 提交: KamioRinn
- 2025.06.11 [Commit#dd2b9253](https://github.com/RVC-Boss/GPT-SoVITS/commit/dd2b9253aabb09db32db7a3344570ed9df043351)
+- 2025.06.11 [PR#2450](https://github.com/RVC-Boss/GPT-SoVITS/pull/2450)
  - 内容: 修复并行推理对v2pro支持bug
  - 类型: 修复
  - 提交: YYuX-1145
@ -606,21 +606,132 @@
  - 内容: v2pro对ge提取时会出现数值溢出的问题修复
  - 类型: 修复
  - 提交: RVC-Boss
- 2025.06.11 [Commit#37f5abfc](https://github.com/RVC-Boss/GPT-SoVITS/commit/6fdc67ca83418306f11e90b9139278313ac5c3e9)[Commit#6fdc67ca](https://github.com/RVC-Boss/GPT-SoVITS/commit/37f5abfcb4a6553652235909db2e124b6f8ff3a5)
+- 2025.06.17 [PR#2464](https://github.com/RVC-Boss/GPT-SoVITS/pull/2464) [PR#2482](https://github.com/RVC-Boss/GPT-SoVITS/pull/2482)
  - 内容: install.sh逻辑优化
  - 类型: 优化
  - 提交: XXXXRT666
- 2025.06.27 [Commit#90ebefa7](https://github.com/RVC-Boss/GPT-SoVITS/commit/90ebefa78fd544da36eebe0b2003620879c921b0)
+- 2025.06.27 [PR#2489](https://github.com/RVC-Boss/GPT-SoVITS/pull/2489)
  - 内容: onnxruntime加载逻辑优化（对gpu/cpu的判断）
  - 类型: 优化
  - 提交: KamioRinn
- 2025.06.27 [Commit#6df61f58](https://github.com/RVC-Boss/GPT-SoVITS/commit/6df61f58e4d18d4c2ad9d1eddd6a1bd690034c23)
+- 2025.06.27 [PR#2488](https://github.com/RVC-Boss/GPT-SoVITS/pull/2488)
  - 内容: 语言分割及格式化优化
  - 类型: 优化
  - 提交: KamioRinn
+
+## 202507
+
 - 2025.07.10 [Commit#426e1a2bb](https://github.com/RVC-Boss/GPT-SoVITS/commit/426e1a2bb43614af2479b877c37acfb0591e952f)
  - 内容: 提升推理进程优先级（修复win11下可能GPU利用率受限的问题）
-  - 类型: 修复
+  - 类型: 优化
  - 提交: XianYue0125
+- 2025.07.16 [PR#2490](https://github.com/RVC-Boss/GPT-SoVITS/pull/2490)
+  - 内容: 解决 TTS.py 无法识别真正支持版本 v2Pro、v2ProPlus 的问题, 同时更新一版默认配置。
+  - 类型: 修复
+  - 提交: jiangsier-xyz
+- 2025.07.16 [Commit#4d8ebf85](https://github.com/RVC-Boss/GPT-SoVITS/commit/4d8ebf85233d4f1166d7cc02fdc595602975ca8f)
+  - 内容: 修复并行推理模式下v2pro模型识别问题
+  - 类型: 修复
+  - 提交: RVC-Boss
+- 2025.07.17 [PR#2531](https://github.com/RVC-Boss/GPT-SoVITS/pull/2531)
+  - 内容: whisper asr支持性价比更高的distill模型
+  - 类型: 优化
+  - 提交: XXXXRT666
+- 2025.07.18 [PR#2536](https://github.com/RVC-Boss/GPT-SoVITS/pull/2536)
+  - 内容: 优化TTS_Config的代码逻辑
+  - 类型: 优化
+  - 提交: ChasonJiang
+- 2025.07.18 [PR#2537](https://github.com/RVC-Boss/GPT-SoVITS/pull/2537)
+  - 内容: 修复gpt的loss计算问题
+  - 类型: 修复
+  - 提交: ChasonJiang

+## 202508

+- 2025.08.02 [PR#2561](https://github.com/RVC-Boss/GPT-SoVITS/pull/2561)
+  - 内容: WSL Rocm
+  - 类型: 修复
+  - 提交: XXXXRT666
+
+## 202509
+
+- 2025.09.10 [Commit#11aa78bd](https://github.com/RVC-Boss/GPT-SoVITS/commit/11aa78bd9bda8b53047cfcae03abf7ca94d27391)
+  - 内容: 修复环境变量可能不为str的问题
+  - 类型: 修复
+  - 提交: RVC-Boss
+
+## 202511
+
+- 2025.11.28 [PR#2671](https://github.com/RVC-Boss/GPT-SoVITS/pull/2671) [PR#2678](https://github.com/RVC-Boss/GPT-SoVITS/pull/2678)
+  - 内容: 流式推理
+  - 类型: 新功能
+  - 提交: ChasonJiang
+- 2025.11.28 [PR#2636](https://github.com/RVC-Boss/GPT-SoVITS/pull/2636)
+  - 内容: 数学计算文本前端逻辑优化
+  - 类型: 优化
+  - 提交: KamioRinn
+- 2025.11.28 [PR#2469](https://github.com/RVC-Boss/GPT-SoVITS/pull/2469)
+  - 内容: 流式推理
+  - 类型: 新功能
+  - 提交: L-jasmine
+- 2025.11.28 [PR#2577](https://github.com/RVC-Boss/GPT-SoVITS/pull/2577)
+  - 内容: 支持vq分布式训练
+  - 类型: 优化
+  - 提交: wzy3650
+- 2025.11.28 [PR#2627](https://github.com/RVC-Boss/GPT-SoVITS/pull/2627) [PR#2679](https://github.com/RVC-Boss/GPT-SoVITS/pull/2679)
+  - 内容: ASR模型下载逻辑优化
+  - 类型: 优化
+  - 提交: XXXXRT666
+- 2025.11.28 [PR#2662](https://github.com/RVC-Boss/GPT-SoVITS/pull/2662)
+  - 内容: default batch size bug 修复
+  - 类型: 修复
+  - 提交: Spr-Aachen
+
+## 202512
+
+- 2025.12.30 [PR#2703](https://github.com/RVC-Boss/GPT-SoVITS/pull/2703) [PR#2704](https://github.com/RVC-Boss/GPT-SoVITS/pull/2704)
+  - 内容: 修复采样错误
+  - 类型: 修复
+  - 提交: ChasonJiang
+
+## 202602
+
+- 2026.02.08 [PR#2727](https://github.com/RVC-Boss/GPT-SoVITS/pull/2727)
+  - 内容: 修复 Conda 条款未同意导致的构建失败
+  - 类型: 修复
+  - 提交: Oarora
+- 2026.02.09 [PR#2732](https://github.com/RVC-Boss/GPT-SoVITS/pull/2732)
+  - 内容: 环境自动构建优化
+  - 类型: 优化
+  - 提交: XXXXRT666
+
+## 202604
+
+- 2026.04.18 [PR#2763](https://github.com/RVC-Boss/GPT-SoVITS/pull/2763)
+  - 内容: 优化 G2PW 的推理输入构造与多音字处理流程，减少重复计算，降低长句场景下的推理开销
+  - 类型: 优化
+  - 提交: baicai-1145
+- 2026.04.18 [PR#2767](https://github.com/RVC-Boss/GPT-SoVITS/pull/2767)
+  - 内容: 改进 Windows 单卡 v3 LoRA 训练流程
+  - 类型: 优化
+  - 提交: 2409324124
+- 2026.04.18 [PR#2755](https://github.com/RVC-Boss/GPT-SoVITS/pull/2755)
+  - 内容: 修复多个模块中的独立 bug
+  - 类型: 修复
+  - 提交: wishhyt
+- 2026.04.18 [PR#2758](https://github.com/RVC-Boss/GPT-SoVITS/pull/2758)
+  - 内容: 添加数据集的错误处理提示
+  - 类型: 优化
+  - 提交: mushroomcowisheggs
+- 2026.04.18 [PR#2753](https://github.com/RVC-Boss/GPT-SoVITS/pull/2753)
+  - 内容: 并行推理部分bug修复
+  - 类型: 修复
+  - 提交: wishhyt
+- 2026.04.18 [PR#2733](https://github.com/RVC-Boss/GPT-SoVITS/pull/2733)
+  - 内容: bug修复：DPO 训练不支持漏字模拟
+  - 类型: 修复
+  - 提交: Mr-Neutr0n
+- 2026.04.18 [Commit#02425ea](https://github.com/RVC-Boss/GPT-SoVITS/commit/02425ea25680c26c700be0bc158756c69103d827)
+  - 内容: 修复onnx脚本未导入Optional等的问题
+  - 类型: 修复
+  - 提交: RVC-Boss
--- a/docs/en/Changelog_EN.md
+++ b/docs/en/Changelog_EN.md
@ -578,3 +578,160 @@
  - Content: Optimized automatic precision detection logic; added collapsible functionality to WebUI frontend modules.
  - Type: New Feature
  - Contributors: XXXXRT666, RVC-Boss
+- 2025.06.06 [PR#2427](https://github.com/RVC-Boss/GPT-SoVITS/pull/2427)
+  - Content: Fix polyphone detection for "X一X" pattern
+  - Type: Fix
+  - Contributor: wzy3650
+- 2025.06.05 [PR#2439](https://github.com/RVC-Boss/GPT-SoVITS/pull/2439)
+  - Content: Config fix; fix SoVITS model loading
+  - Type: Fix
+  - Contributor: wzy3650
+- 2025.06.09 [Commit#8056efe4](https://github.com/RVC-Boss/GPT-SoVITS/commit/8056efe4ab7bbc3610c72ae356a6f37518441f7d)
+  - Content: Fix possible numerical explosion of `ge.sum` causing silent inference
+  - Type: Fix
+  - Contributor: RVC-Boss
+- 2025.06.10 [Commit#2c0436b9](https://github.com/RVC-Boss/GPT-SoVITS/commit/2c0436b9ce397424ae03476c836fb64c6e5ebcc6)
+  - Content: Fix incorrect Windows path when experiment name ends with a space
+  - Type: Fix
+  - Contributor: RVC-Boss
+- 2025.06.10 [PR#2449](https://github.com/RVC-Boss/GPT-SoVITS/pull/2449)
+  - Content: Optimize language segmentation
+  - Type: Optimization
+  - Contributor: KamioRinn
+- 2025.06.11 [PR#2450](https://github.com/RVC-Boss/GPT-SoVITS/pull/2450)
+  - Content: Fix bug in parallel inference support for v2pro
+  - Type: Fix
+  - Contributor: YYuX-1145
+- 2025.06.11 [Commit#ed89a023](https://github.com/RVC-Boss/GPT-SoVITS/commit/ed89a023378dabba9d4b6580235bb9742245816d)
+  - Content: Fix numerical overflow issue when extracting `ge` for v2pro
+  - Type: Fix
+  - Contributor: RVC-Boss
+- 2025.06.17 [PR#2464](https://github.com/RVC-Boss/GPT-SoVITS/pull/2464) [PR#2482](https://github.com/RVC-Boss/GPT-SoVITS/pull/2482)
+  - Content: Optimize `install.sh` logic
+  - Type: Optimization
+  - Contributor: XXXXRT666
+- 2025.06.27 [PR#2489](https://github.com/RVC-Boss/GPT-SoVITS/pull/2489)
+  - Content: Optimize onnxruntime loading logic (GPU/CPU detection)
+  - Type: Optimization
+  - Contributor: KamioRinn
+- 2025.06.27 [PR#2488](https://github.com/RVC-Boss/GPT-SoVITS/pull/2488)
+  - Content: Optimize language segmentation and formatting
+  - Type: Optimization
+  - Contributor: KamioRinn
+
+## 202507
+
+- 2025.07.10 [Commit#426e1a2bb](https://github.com/RVC-Boss/GPT-SoVITS/commit/426e1a2bb43614af2479b877c37acfb0591e952f)
+  - Content: Increase inference process priority (fix possible GPU utilization limitation on Win11)
+  - Type: Optimization
+  - Contributor: XianYue0125
+- 2025.07.16 [PR#2490](https://github.com/RVC-Boss/GPT-SoVITS/pull/2490)
+  - Content: Fix TTS.py not recognizing actually supported versions v2Pro and v2ProPlus, and update default configuration
+  - Type: Fix
+  - Contributor: jiangsier-xyz
+- 2025.07.16 [Commit#4d8ebf85](https://github.com/RVC-Boss/GPT-SoVITS/commit/4d8ebf85233d4f1166d7cc02fdc595602975ca8f)
+  - Content: Fix v2pro model recognition issue in parallel inference mode
+  - Type: Fix
+  - Contributor: RVC-Boss
+- 2025.07.17 [PR#2531](https://github.com/RVC-Boss/GPT-SoVITS/pull/2531)
+  - Content: Whisper ASR supports more cost-effective distill models
+  - Type: Optimization
+  - Contributor: XXXXRT666
+- 2025.07.18 [PR#2536](https://github.com/RVC-Boss/GPT-SoVITS/pull/2536)
+  - Content: Optimize `TTS_Config` code logic
+  - Type: Optimization
+  - Contributor: ChasonJiang
+- 2025.07.18 [PR#2537](https://github.com/RVC-Boss/GPT-SoVITS/pull/2537)
+  - Content: Fix GPT loss calculation issue
+  - Type: Fix
+  - Contributor: ChasonJiang
+
+## 202508
+
+- 2025.08.02 [PR#2561](https://github.com/RVC-Boss/GPT-SoVITS/pull/2561)
+  - Content: WSL Rocm
+  - Type: Fix
+  - Contributor: XXXXRT666
+
+## 202509
+
+- 2025.09.10 [Commit#11aa78bd](https://github.com/RVC-Boss/GPT-SoVITS/commit/11aa78bd9bda8b53047cfcae03abf7ca94d27391)
+  - Content: Fix issue where environment variable may not be a string
+  - Type: Fix
+  - Contributor: RVC-Boss
+
+## 202511
+
+- 2025.11.28 [PR#2671](https://github.com/RVC-Boss/GPT-SoVITS/pull/2671) [PR#2678](https://github.com/RVC-Boss/GPT-SoVITS/pull/2678)
+  - Content: Streaming inference
+  - Type: New Feature
+  - Contributor: ChasonJiang
+- 2025.11.28 [PR#2636](https://github.com/RVC-Boss/GPT-SoVITS/pull/2636)
+  - Content: Optimize text frontend logic for mathematical expression text
+  - Type: Optimization
+  - Contributor: KamioRinn
+- 2025.11.28 [PR#2469](https://github.com/RVC-Boss/GPT-SoVITS/pull/2469)
+  - Content: Streaming inference
+  - Type: New Feature
+  - Contributor: L-jasmine
+- 2025.11.28 [PR#2577](https://github.com/RVC-Boss/GPT-SoVITS/pull/2577)
+  - Content: Support VQ distributed training
+  - Type: Optimization
+  - Contributor: wzy3650
+- 2025.11.28 [PR#2627](https://github.com/RVC-Boss/GPT-SoVITS/pull/2627) [PR#2679](https://github.com/RVC-Boss/GPT-SoVITS/pull/2679)
+  - Content: Optimize ASR model download logic
+  - Type: Optimization
+  - Contributor: XXXXRT666
+- 2025.11.28 [PR#2662](https://github.com/RVC-Boss/GPT-SoVITS/pull/2662)
+  - Content: Fix default batch size bug
+  - Type: Fix
+  - Contributor: Spr-Aachen
+
+## 202512
+
+- 2025.12.30 [PR#2703](https://github.com/RVC-Boss/GPT-SoVITS/pull/2703) [PR#2704](https://github.com/RVC-Boss/GPT-SoVITS/pull/2704)
+  - Content: Fix sampling error
+  - Type: Fix
+  - Contributor: ChasonJiang
+
+## 202602
+
+- 2026.02.08 [PR#2727](https://github.com/RVC-Boss/GPT-SoVITS/pull/2727)
+  - Content: Fix build failure caused by unaccepted Conda terms
+  - Type: Fix
+  - Contributor: Oarora
+- 2026.02.09 [PR#2732](https://github.com/RVC-Boss/GPT-SoVITS/pull/2732)
+  - Content: Optimize automatic environment setup
+  - Type: Optimization
+  - Contributor: XXXXRT666
+
+## 202604
+
+- 2026.04.18 [PR#2763](https://github.com/RVC-Boss/GPT-SoVITS/pull/2763)
+  - Content: Optimize G2PW inference input construction and polyphone handling to reduce redundant computation and inference overhead for long sentences
+  - Type: Optimization
+  - Contributor: baicai-1145
+- 2026.04.18 [PR#2767](https://github.com/RVC-Boss/GPT-SoVITS/pull/2767)
+  - Content: Improve the LoRA training flow for GPT-SoVITS v3 on a single card under Windows
+  - Type: Optimization
+  - Contributor: 2409324124
+- 2026.04.18 [PR#2755](https://github.com/RVC-Boss/GPT-SoVITS/pull/2755)
+  - Content: Fix miscellaneous bugs in multiple modules
+  - Type: Fix
+  - Contributor: wishhyt
+- 2026.04.18 [PR#2758](https://github.com/RVC-Boss/GPT-SoVITS/pull/2758)
+  - Content: Add error handling hints for dataset processing
+  - Type: Optimization
+  - Contributor: mushroomcowisheggs
+- 2026.04.18 [PR#2753](https://github.com/RVC-Boss/GPT-SoVITS/pull/2753)
+  - Content: Fix some bugs in parallel inference
+  - Type: Fix
+  - Contributor: wishhyt
+- 2026.04.18 [PR#2733](https://github.com/RVC-Boss/GPT-SoVITS/pull/2733)
+  - Content: Fix bug where DPO training does not support missing word simulation
+  - Type: Fix
+  - Contributor: Mr-Neutr0n
+- 2026.04.18 [Commit#02425ea](https://github.com/RVC-Boss/GPT-SoVITS/commit/02425ea25680c26c700be0bc158756c69103d827)
+  - Content: Fix missing imports (e.g., Optional) in ONNX script
+  - Type: Fix
+  - Contributor: RVC-Boss
--- a/docs/ja/Changelog_JA.md
+++ b/docs/ja/Changelog_JA.md
@ -578,3 +578,160 @@
  - 内容: 自動精度検出ロジックを最適化し、WebUI フロントエンドモジュールに折り畳み（Collapsible）機能を追加
  - タイプ: 新機能
  - 貢献者: XXXXRT666, RVC-Boss
+- 2025.06.06 [PR#2427](https://github.com/RVC-Boss/GPT-SoVITS/pull/2427)
+  - 内容: 「X一X」パターンの多音字検出を修正
+  - タイプ: 修正
+  - 貢献者: wzy3650
+- 2025.06.05 [PR#2439](https://github.com/RVC-Boss/GPT-SoVITS/pull/2439)
+  - 内容: 設定の修正；SoVITSモデル読み込みの修正
+  - タイプ: 修正
+  - 貢献者: wzy3650
+- 2025.06.09 [Commit#8056efe4](https://github.com/RVC-Boss/GPT-SoVITS/commit/8056efe4ab7bbc3610c72ae356a6f37518441f7d)
+  - 内容: `ge.sum`の数値爆発による推論の無音化を修正
+  - タイプ: 修正
+  - 貢献者: RVC-Boss
+- 2025.06.10 [Commit#2c0436b9](https://github.com/RVC-Boss/GPT-SoVITS/commit/2c0436b9ce397424ae03476c836fb64c6e5ebcc6)
+  - 内容: 実験名がスペースで終わる場合のWindowsパスの誤りを修正
+  - タイプ: 修正
+  - 貢献者: RVC-Boss
+- 2025.06.10 [PR#2449](https://github.com/RVC-Boss/GPT-SoVITS/pull/2449)
+  - 内容: 言語分割の最適化
+  - タイプ: 最適化
+  - 貢献者: KamioRinn
+- 2025.06.11 [PR#2450](https://github.com/RVC-Boss/GPT-SoVITS/pull/2450)
+  - 内容: v2proの並列推論対応におけるバグを修正
+  - タイプ: 修正
+  - 貢献者: YYuX-1145
+- 2025.06.11 [Commit#ed89a023](https://github.com/RVC-Boss/GPT-SoVITS/commit/ed89a023378dabba9d4b6580235bb9742245816d)
+  - 内容: v2proの`ge`抽出時の数値オーバーフロー問題を修正
+  - タイプ: 修正
+  - 貢献者: RVC-Boss
+- 2025.06.17 [PR#2464](https://github.com/RVC-Boss/GPT-SoVITS/pull/2464) [PR#2482](https://github.com/RVC-Boss/GPT-SoVITS/pull/2482)
+  - 内容: `install.sh`のロジックを最適化
+  - タイプ: 最適化
+  - 貢献者: XXXXRT666
+- 2025.06.27 [PR#2489](https://github.com/RVC-Boss/GPT-SoVITS/pull/2489)
+  - 内容: onnxruntime読み込みロジックを最適化（GPU/CPU検出）
+  - タイプ: 最適化
+  - 貢献者: KamioRinn
+- 2025.06.27 [PR#2488](https://github.com/RVC-Boss/GPT-SoVITS/pull/2488)
+  - 内容: 言語分割と書式を最適化
+  - タイプ: 最適化
+  - 貢献者: KamioRinn
+
+## 202507
+
+- 2025.07.10 [Commit#426e1a2bb](https://github.com/RVC-Boss/GPT-SoVITS/commit/426e1a2bb43614af2479b877c37acfb0591e952f)
+  - 内容: 推論プロセスの優先度を上げる（Win11でのGPU利用制限の可能性を修正）
+  - タイプ: 最適化
+  - 貢献者: XianYue0125
+- 2025.07.16 [PR#2490](https://github.com/RVC-Boss/GPT-SoVITS/pull/2490)
+  - 内容: TTS.pyが実際にサポートされているバージョンv2Proおよびv2ProPlusを認識しない問題を修正し、デフォルト設定を更新
+  - タイプ: 修正
+  - 貢献者: jiangsier-xyz
+- 2025.07.16 [Commit#4d8ebf85](https://github.com/RVC-Boss/GPT-SoVITS/commit/4d8ebf85233d4f1166d7cc02fdc595602975ca8f)
+  - 内容: 並列推論モードでのv2proモデル認識問題を修正
+  - タイプ: 修正
+  - 貢献者: RVC-Boss
+- 2025.07.17 [PR#2531](https://github.com/RVC-Boss/GPT-SoVITS/pull/2531)
+  - 内容: Whisper ASRがよりコスト効率の高い蒸留モデルをサポート
+  - タイプ: 最適化
+  - 貢献者: XXXXRT666
+- 2025.07.18 [PR#2536](https://github.com/RVC-Boss/GPT-SoVITS/pull/2536)
+  - 内容: `TTS_Config`のコードロジックを最適化
+  - タイプ: 最適化
+  - 貢献者: ChasonJiang
+- 2025.07.18 [PR#2537](https://github.com/RVC-Boss/GPT-SoVITS/pull/2537)
+  - 内容: GPT損失計算の問題を修正
+  - タイプ: 修正
+  - 貢献者: ChasonJiang
+
+## 202508
+
+- 2025.08.02 [PR#2561](https://github.com/RVC-Boss/GPT-SoVITS/pull/2561)
+  - 内容: WSL Rocm対応
+  - タイプ: 修正
+  - 貢献者: XXXXRT666
+
+## 202509
+
+- 2025.09.10 [Commit#11aa78bd](https://github.com/RVC-Boss/GPT-SoVITS/commit/11aa78bd9bda8b53047cfcae03abf7ca94d27391)
+  - 内容: 環境変数が文字列でない可能性がある問題を修正
+  - タイプ: 修正
+  - 貢献者: RVC-Boss
+
+## 202511
+
+- 2025.11.28 [PR#2671](https://github.com/RVC-Boss/GPT-SoVITS/pull/2671) [PR#2678](https://github.com/RVC-Boss/GPT-SoVITS/pull/2678)
+  - 内容: ストリーミング推論
+  - タイプ: 新機能
+  - 貢献者: ChasonJiang
+- 2025.11.28 [PR#2636](https://github.com/RVC-Boss/GPT-SoVITS/pull/2636)
+  - 内容: 数式テキストに対するテキスト前処理ロジックを最適化
+  - タイプ: 最適化
+  - 貢献者: KamioRinn
+- 2025.11.28 [PR#2469](https://github.com/RVC-Boss/GPT-SoVITS/pull/2469)
+  - 内容: ストリーミング推論
+  - タイプ: 新機能
+  - 貢献者: L-jasmine
+- 2025.11.28 [PR#2577](https://github.com/RVC-Boss/GPT-SoVITS/pull/2577)
+  - 内容: VQ分散学習をサポート
+  - タイプ: 最適化
+  - 貢献者: wzy3650
+- 2025.11.28 [PR#2627](https://github.com/RVC-Boss/GPT-SoVITS/pull/2627) [PR#2679](https://github.com/RVC-Boss/GPT-SoVITS/pull/2679)
+  - 内容: ASRモデルダウンロードロジックを最適化
+  - タイプ: 最適化
+  - 貢献者: XXXXRT666
+- 2025.11.28 [PR#2662](https://github.com/RVC-Boss/GPT-SoVITS/pull/2662)
+  - 内容: デフォルトのバッチサイズのバグを修正
+  - タイプ: 修正
+  - 貢献者: Spr-Aachen
+
+## 202512
+
+- 2025.12.30 [PR#2703](https://github.com/RVC-Boss/GPT-SoVITS/pull/2703) [PR#2704](https://github.com/RVC-Boss/GPT-SoVITS/pull/2704)
+  - 内容: サンプリングエラーを修正
+  - タイプ: 修正
+  - 貢献者: ChasonJiang
+
+## 202602
+
+- 2026.02.08 [PR#2727](https://github.com/RVC-Boss/GPT-SoVITS/pull/2727)
+  - 内容: 受け入れられなかったConda利用規約によるビルド失敗を修正
+  - タイプ: 修正
+  - 貢献者: Oarora
+- 2026.02.09 [PR#2732](https://github.com/RVC-Boss/GPT-SoVITS/pull/2732)
+  - 内容: 自動環境セットアップを最適化
+  - タイプ: 最適化
+  - 貢献者: XXXXRT666
+
+## 202604
+
+- 2026.04.18 [PR#2763](https://github.com/RVC-Boss/GPT-SoVITS/pull/2763)
+  - 内容: G2PW推論入力の構築と多音字処理を最適化し、長文における冗長な計算と推論オーバーヘッドを削減
+  - タイプ: 最適化
+  - 貢献者: baicai-1145
+- 2026.04.18 [PR#2767](https://github.com/RVC-Boss/GPT-SoVITS/pull/2767)
+  - 内容: WindowsでのシングルカードにおけるGPT-SoVITS v3のLoRAトレーニングフローを改善
+  - タイプ: 最適化
+  - 貢献者: 2409324124
+- 2026.04.18 [PR#2755](https://github.com/RVC-Boss/GPT-SoVITS/pull/2755)
+  - 内容: 複数モジュールの雑多なバグを修正
+  - タイプ: 修正
+  - 貢献者: wishhyt
+- 2026.04.18 [PR#2758](https://github.com/RVC-Boss/GPT-SoVITS/pull/2758)
+  - 内容: データセット処理時のエラーハンドリングヒントを追加
+  - タイプ: 最適化
+  - 貢献者: mushroomcowisheggs
+- 2026.04.18 [PR#2753](https://github.com/RVC-Boss/GPT-SoVITS/pull/2753)
+  - 内容: 並列推論の一部バグを修正
+  - タイプ: 修正
+  - 貢献者: wishhyt
+- 2026.04.18 [PR#2733](https://github.com/RVC-Boss/GPT-SoVITS/pull/2733)
+  - 内容: DPOトレーニングが欠落単語シミュレーションをサポートしないバグを修正
+  - タイプ: 修正
+  - 貢献者: Mr-Neutr0n
+- 2026.04.18 [Commit#02425ea](https://github.com/RVC-Boss/GPT-SoVITS/commit/02425ea25680c26c700be0bc158756c69103d827)
+  - 内容: ONNXスクリプトでの（Optionalなどの）不足インポートを修正
+  - タイプ: 修正
+  - 貢献者: RVC-Boss
--- a/docs/ko/Changelog_KO.md
+++ b/docs/ko/Changelog_KO.md
@ -578,3 +578,160 @@
  - 내용: 자동 정밀도 감지 로직 최적화; WebUI 프론트엔드 모듈에 접기 기능 추가
  - 유형: 신규 기능
  - 기여자: XXXXRT666, RVC-Boss
+- 2025.06.06 [PR#2427](https://github.com/RVC-Boss/GPT-SoVITS/pull/2427)
+  - 내용: "X一X" 패턴의 다중 발음 감지 오류 수정
+  - 유형: 수정
+  - 기여자: wzy3650
+- 2025.06.05 [PR#2439](https://github.com/RVC-Boss/GPT-SoVITS/pull/2439)
+  - 내용: 설정 오류 수정; SoVITS 모델 로딩 오류 수정
+  - 유형: 수정
+  - 기여자: wzy3650
+- 2025.06.09 [Commit#8056efe4](https://github.com/RVC-Boss/GPT-SoVITS/commit/8056efe4ab7bbc3610c72ae356a6f37518441f7d)
+  - 내용: `ge.sum`의 수치 폭발 가능성으로 인한 추론 무음 현상 수정
+  - 유형: 수정
+  - 기여자: RVC-Boss
+- 2025.06.10 [Commit#2c0436b9](https://github.com/RVC-Boss/GPT-SoVITS/commit/2c0436b9ce397424ae03476c836fb64c6e5ebcc6)
+  - 내용: 실험 이름이 공백으로 끝날 때 발생하는 잘못된 Windows 경로 문제 수정
+  - 유형: 수정
+  - 기여자: RVC-Boss
+- 2025.06.10 [PR#2449](https://github.com/RVC-Boss/GPT-SoVITS/pull/2449)
+  - 내용: 언어 분할 최적화
+  - 유형: 최적화
+  - 기여자: KamioRinn
+- 2025.06.11 [PR#2450](https://github.com/RVC-Boss/GPT-SoVITS/pull/2450)
+  - 내용: v2pro 병렬 추론 지원 버그 수정
+  - 유형: 수정
+  - 기여자: YYuX-1145
+- 2025.06.11 [Commit#ed89a023](https://github.com/RVC-Boss/GPT-SoVITS/commit/ed89a023378dabba9d4b6580235bb9742245816d)
+  - 내용: v2pro의 `ge` 추출 시 수치 오버플로우 문제 수정
+  - 유형: 수정
+  - 기여자: RVC-Boss
+- 2025.06.17 [PR#2464](https://github.com/RVC-Boss/GPT-SoVITS/pull/2464) [PR#2482](https://github.com/RVC-Boss/GPT-SoVITS/pull/2482)
+  - 내용: `install.sh` 로직 최적화
+  - 유형: 최적화
+  - 기여자: XXXXRT666
+- 2025.06.27 [PR#2489](https://github.com/RVC-Boss/GPT-SoVITS/pull/2489)
+  - 내용: onnxruntime 로딩 로직 최적화 (GPU/CPU 감지)
+  - 유형: 최적화
+  - 기여자: KamioRinn
+- 2025.06.27 [PR#2488](https://github.com/RVC-Boss/GPT-SoVITS/pull/2488)
+  - 내용: 언어 분할 및 형식 최적화
+  - 유형: 최적화
+  - 기여자: KamioRinn
+
+## 202507
+
+- 2025.07.10 [Commit#426e1a2bb](https://github.com/RVC-Boss/GPT-SoVITS/commit/426e1a2bb43614af2479b877c37acfb0591e952f)
+  - 내용: 추론 프로세스 우선순위 증가 (Win11에서 GPU 활용 제한 가능성 수정)
+  - 유형: 최적화
+  - 기여자: XianYue0125
+- 2025.07.16 [PR#2490](https://github.com/RVC-Boss/GPT-SoVITS/pull/2490)
+  - 내용: TTS.py가 실제 지원되는 버전 v2Pro 및 v2ProPlus를 인식하지 못하는 문제 수정 및 기본 설정 업데이트
+  - 유형: 수정
+  - 기여자: jiangsier-xyz
+- 2025.07.16 [Commit#4d8ebf85](https://github.com/RVC-Boss/GPT-SoVITS/commit/4d8ebf85233d4f1166d7cc02fdc595602975ca8f)
+  - 내용: 병렬 추론 모드에서 v2pro 모델 인식 문제 수정
+  - 유형: 수정
+  - 기여자: RVC-Boss
+- 2025.07.17 [PR#2531](https://github.com/RVC-Boss/GPT-SoVITS/pull/2531)
+  - 내용: Whisper ASR이 더 비용 효율적인 distill 모델 지원
+  - 유형: 최적화
+  - 기여자: XXXXRT666
+- 2025.07.18 [PR#2536](https://github.com/RVC-Boss/GPT-SoVITS/pull/2536)
+  - 내용: `TTS_Config` 코드 로직 최적화
+  - 유형: 최적화
+  - 기여자: ChasonJiang
+- 2025.07.18 [PR#2537](https://github.com/RVC-Boss/GPT-SoVITS/pull/2537)
+  - 내용: GPT 손실(loss) 계산 문제 수정
+  - 유형: 수정
+  - 기여자: ChasonJiang
+
+## 202508
+
+- 2025.08.02 [PR#2561](https://github.com/RVC-Boss/GPT-SoVITS/pull/2561)
+  - 내용: WSL Rocm
+  - 유형: 수정
+  - 기여자: XXXXRT666
+
+## 202509
+
+- 2025.09.10 [Commit#11aa78bd](https://github.com/RVC-Boss/GPT-SoVITS/commit/11aa78bd9bda8b53047cfcae03abf7ca94d27391)
+  - 내용: 환경 변수가 문자열이 아닐 수 있는 문제 수정
+  - 유형: 수정
+  - 기여자: RVC-Boss
+
+## 202511
+
+- 2025.11.28 [PR#2671](https://github.com/RVC-Boss/GPT-SoVITS/pull/2671) [PR#2678](https://github.com/RVC-Boss/GPT-SoVITS/pull/2678)
+  - 내용: 스트리밍 추론
+  - 유형: 새 기능
+  - 기여자: ChasonJiang
+- 2025.11.28 [PR#2636](https://github.com/RVC-Boss/GPT-SoVITS/pull/2636)
+  - 내용: 수학 표현식 텍스트에 대한 텍스트 전처리 로직 최적화
+  - 유형: 최적화
+  - 기여자: KamioRinn
+- 2025.11.28 [PR#2469](https://github.com/RVC-Boss/GPT-SoVITS/pull/2469)
+  - 내용: 스트리밍 추론
+  - 유형: 새 기능
+  - 기여자: L-jasmine
+- 2025.11.28 [PR#2577](https://github.com/RVC-Boss/GPT-SoVITS/pull/2577)
+  - 내용: VQ 분산 학습 지원
+  - 유형: 최적화
+  - 기여자: wzy3650
+- 2025.11.28 [PR#2627](https://github.com/RVC-Boss/GPT-SoVITS/pull/2627) [PR#2679](https://github.com/RVC-Boss/GPT-SoVITS/pull/2679)
+  - 내용: ASR 모델 다운로드 로직 최적화
+  - 유형: 최적화
+  - 기여자: XXXXRT666
+- 2025.11.28 [PR#2662](https://github.com/RVC-Boss/GPT-SoVITS/pull/2662)
+  - 내용: 기본 배치 크기 버그 수정
+  - 유형: 수정
+  - 기여자: Spr-Aachen
+
+## 202512
+
+- 2025.12.30 [PR#2703](https://github.com/RVC-Boss/GPT-SoVITS/pull/2703) [PR#2704](https://github.com/RVC-Boss/GPT-SoVITS/pull/2704)
+  - 내용: 샘플링 오류 수정
+  - 유형: 수정
+  - 기여자: ChasonJiang
+
+## 202602
+
+- 2026.02.08 [PR#2727](https://github.com/RVC-Boss/GPT-SoVITS/pull/2727)
+  - 내용: Conda 약관 미동의로 인한 빌드 실패 수정
+  - 유형: 수정
+  - 기여자: Oarora
+- 2026.02.09 [PR#2732](https://github.com/RVC-Boss/GPT-SoVITS/pull/2732)
+  - 내용: 자동 환경 설정 최적화
+  - 유형: 최적화
+  - 기여자: XXXXRT666
+
+## 202604
+
+- 2026.04.18 [PR#2763](https://github.com/RVC-Boss/GPT-SoVITS/pull/2763)
+  - 내용: G2PW 추론 입력 구성 및 다중 발음 처리를 최적화하여 긴 문장에 대한 중복 계산 및 추론 오버헤드 감소
+  - 유형: 최적화
+  - 기여자: baicai-1145
+- 2026.04.18 [PR#2767](https://github.com/RVC-Boss/GPT-SoVITS/pull/2767)
+  - 내용: Windows 환경 단일 GPU에서 GPT-SoVITS v3의 LoRA 학습 흐름 개선
+  - 유형: 최적화
+  - 기여자: 2409324124
+- 2026.04.18 [PR#2755](https://github.com/RVC-Boss/GPT-SoVITS/pull/2755)
+  - 내용: 여러 모듈의 잡다한 버그 수정
+  - 유형: 수정
+  - 기여자: wishhyt
+- 2026.04.18 [PR#2758](https://github.com/RVC-Boss/GPT-SoVITS/pull/2758)
+  - 내용: 데이터셋 처리를 위한 오류 처리 힌트 추가
+  - 유형: 최적화
+  - 기여자: mushroomcowisheggs
+- 2026.04.18 [PR#2753](https://github.com/RVC-Boss/GPT-SoVITS/pull/2753)
+  - 내용: 병렬 추론의 일부 버그 수정
+  - 유형: 수정
+  - 기여자: wishhyt
+- 2026.04.18 [PR#2733](https://github.com/RVC-Boss/GPT-SoVITS/pull/2733)
+  - 내용: DPO 학습이 누락 단어 시뮬레이션을 지원하지 않는 버그 수정
+  - 유형: 수정
+  - 기여자: Mr-Neutr0n
+- 2026.04.18 [Commit#02425ea](https://github.com/RVC-Boss/GPT-SoVITS/commit/02425ea25680c26c700be0bc158756c69103d827)
+  - 내용: ONNX 스크립트에서 Optional 등 누락된 임포트 문제 수정
+  - 유형: 수정
+  - 기여자: RVC-Boss
--- a/docs/tr/Changelog_TR.md
+++ b/docs/tr/Changelog_TR.md
@ -2,8 +2,6 @@

 ## 202401

-## 202401
-
 - 2024.01.21 [PR#108](https://github.com/RVC-Boss/GPT-SoVITS/pull/108)
  - İçerik: WebUI'ya İngilizce sistem çeviri desteği eklendi.
  - Tür: Dokümantasyon
@ -332,6 +330,8 @@
  - Tür: Optimizasyon
  - Katkıda Bulunan: RVC-Boss, GoHomeToMacDonal
  - İlgili: [PR#672](https://github.com/RVC-Boss/GPT-SoVITS/pull/672)
+- Gelecek güncellemeler, `fast_inference` dalındaki değişikliklerin tutarlılığını doğrulamaya devam edecek.
+
 - 2024.07.13 [PR#1294](https://github.com/RVC-Boss/GPT-SoVITS/pull/1294), [PR#1298](https://github.com/RVC-Boss/GPT-SoVITS/pull/1298)
  - İçerik: i18n taraması yeniden düzenlendi ve çok dilli yapılandırma dosyaları güncellendi
  - Tür: Dokümantasyon
@ -578,3 +578,160 @@
  - İçerik: Otomatik hassasiyet algılama mantığı optimize edildi; WebUI önyüz modüllerine katlanabilir özellik eklendi
  - Tür: Yeni Özellik
  - Katkıda Bulunanlar: XXXXRT666, RVC-Boss
+- 2025.06.06 [PR#2427](https://github.com/RVC-Boss/GPT-SoVITS/pull/2427)
+  - İçerik: "X一X" kalıbı için çok sesli harf tespitini düzelt
+  - Tür: Düzeltme
+  - Katkıda Bulunan: wzy3650
+- 2025.06.05 [PR#2439](https://github.com/RVC-Boss/GPT-SoVITS/pull/2439)
+  - İçerik: Yapılandırma düzeltmesi; SoVITS model yüklemesini düzelt
+  - Tür: Düzeltme
+  - Katkıda Bulunan: wzy3650
+- 2025.06.09 [Commit#8056efe4](https://github.com/RVC-Boss/GPT-SoVITS/commit/8056efe4ab7bbc3610c72ae356a6f37518441f7d)
+  - İçerik: `ge.sum` kaynaklı olası sayısal patlamayı (sessiz çıkarıma yol açan) düzelt
+  - Tür: Düzeltme
+  - Katkıda Bulunan: RVC-Boss
+- 2025.06.10 [Commit#2c0436b9](https://github.com/RVC-Boss/GPT-SoVITS/commit/2c0436b9ce397424ae03476c836fb64c6e5ebcc6)
+  - İçerik: Deney adı boşlukla bittiğinde oluşan hatalı Windows yolunu düzelt
+  - Tür: Düzeltme
+  - Katkıda Bulunan: RVC-Boss
+- 2025.06.10 [PR#2449](https://github.com/RVC-Boss/GPT-SoVITS/pull/2449)
+  - İçerik: Dil bölütlemeyi optimize et
+  - Tür: Optimizasyon
+  - Katkıda Bulunan: KamioRinn
+- 2025.06.11 [PR#2450](https://github.com/RVC-Boss/GPT-SoVITS/pull/2450)
+  - İçerik: v2pro için paralel çıkarım desteğindeki hatayı düzelt
+  - Tür: Düzeltme
+  - Katkıda Bulunan: YYuX-1145
+- 2025.06.11 [Commit#ed89a023](https://github.com/RVC-Boss/GPT-SoVITS/commit/ed89a023378dabba9d4b6580235bb9742245816d)
+  - İçerik: v2pro için `ge` çıkarımındaki sayısal taşma sorununu düzelt
+  - Tür: Düzeltme
+  - Katkıda Bulunan: RVC-Boss
+- 2025.06.17 [PR#2464](https://github.com/RVC-Boss/GPT-SoVITS/pull/2464) [PR#2482](https://github.com/RVC-Boss/GPT-SoVITS/pull/2482)
+  - İçerik: `install.sh` mantığını optimize et
+  - Tür: Optimizasyon
+  - Katkıda Bulunan: XXXXRT666
+- 2025.06.27 [PR#2489](https://github.com/RVC-Boss/GPT-SoVITS/pull/2489)
+  - İçerik: onnxruntime yükleme mantığını optimize et (GPU/CPU algılama)
+  - Tür: Optimizasyon
+  - Katkıda Bulunan: KamioRinn
+- 2025.06.27 [PR#2488](https://github.com/RVC-Boss/GPT-SoVITS/pull/2488)
+  - İçerik: Dil bölütleme ve biçimlendirmeyi optimize et
+  - Tür: Optimizasyon
+  - Katkıda Bulunan: KamioRinn
+
+## 202507
+
+- 2025.07.10 [Commit#426e1a2bb](https://github.com/RVC-Boss/GPT-SoVITS/commit/426e1a2bb43614af2479b877c37acfb0591e952f)
+  - İçerik: Çıkarım işlem önceliğini artır (Win11'de olası GPU kullanım sınırlamasını düzelt)
+  - Tür: Optimizasyon
+  - Katkıda Bulunan: XianYue0125
+- 2025.07.16 [PR#2490](https://github.com/RVC-Boss/GPT-SoVITS/pull/2490)
+  - İçerik: TTS.py'nin gerçekte desteklenen sürümler olan v2Pro ve v2ProPlus'ı tanımaması sorununu düzelt ve varsayılan yapılandırmayı güncelle
+  - Tür: Düzeltme
+  - Katkıda Bulunan: jiangsier-xyz
+- 2025.07.16 [Commit#4d8ebf85](https://github.com/RVC-Boss/GPT-SoVITS/commit/4d8ebf85233d4f1166d7cc02fdc595602975ca8f)
+  - İçerik: Paralel çıkarım modunda v2pro model tanıma sorununu düzelt
+  - Tür: Düzeltme
+  - Katkıda Bulunan: RVC-Boss
+- 2025.07.17 [PR#2531](https://github.com/RVC-Boss/GPT-SoVITS/pull/2531)
+  - İçerik: Whisper ASR daha uygun maliyetli distill modellerini destekler
+  - Tür: Optimizasyon
+  - Katkıda Bulunan: XXXXRT666
+- 2025.07.18 [PR#2536](https://github.com/RVC-Boss/GPT-SoVITS/pull/2536)
+  - İçerik: `TTS_Config` kod mantığını optimize et
+  - Tür: Optimizasyon
+  - Katkıda Bulunan: ChasonJiang
+- 2025.07.18 [PR#2537](https://github.com/RVC-Boss/GPT-SoVITS/pull/2537)
+  - İçerik: GPT kayıp (loss) hesaplama sorununu düzelt
+  - Tür: Düzeltme
+  - Katkıda Bulunan: ChasonJiang
+
+## 202508
+
+- 2025.08.02 [PR#2561](https://github.com/RVC-Boss/GPT-SoVITS/pull/2561)
+  - İçerik: WSL Rocm
+  - Tür: Düzeltme
+  - Katkıda Bulunan: XXXXRT666
+
+## 202509
+
+- 2025.09.10 [Commit#11aa78bd](https://github.com/RVC-Boss/GPT-SoVITS/commit/11aa78bd9bda8b53047cfcae03abf7ca94d27391)
+  - İçerik: Ortam değişkeninin dize (string) olmaması sorununu düzelt
+  - Tür: Düzeltme
+  - Katkıda Bulunan: RVC-Boss
+
+## 202511
+
+- 2025.11.28 [PR#2671](https://github.com/RVC-Boss/GPT-SoVITS/pull/2671) [PR#2678](https://github.com/RVC-Boss/GPT-SoVITS/pull/2678)
+  - İçerik: Akışlı çıkarım (streaming inference)
+  - Tür: Yeni Özellik
+  - Katkıda Bulunan: ChasonJiang
+- 2025.11.28 [PR#2636](https://github.com/RVC-Boss/GPT-SoVITS/pull/2636)
+  - İçerik: Matematiksel ifade metinleri için metin ön uç (frontend) mantığını optimize et
+  - Tür: Optimizasyon
+  - Katkıda Bulunan: KamioRinn
+- 2025.11.28 [PR#2469](https://github.com/RVC-Boss/GPT-SoVITS/pull/2469)
+  - İçerik: Akışlı çıkarım (streaming inference)
+  - Tür: Yeni Özellik
+  - Katkıda Bulunan: L-jasmine
+- 2025.11.28 [PR#2577](https://github.com/RVC-Boss/GPT-SoVITS/pull/2577)
+  - İçerik: VQ dağıtılmış eğitimi destekle
+  - Tür: Optimizasyon
+  - Katkıda Bulunan: wzy3650
+- 2025.11.28 [PR#2627](https://github.com/RVC-Boss/GPT-SoVITS/pull/2627) [PR#2679](https://github.com/RVC-Boss/GPT-SoVITS/pull/2679)
+  - İçerik: ASR model indirme mantığını optimize et
+  - Tür: Optimizasyon
+  - Katkıda Bulunan: XXXXRT666
+- 2025.11.28 [PR#2662](https://github.com/RVC-Boss/GPT-SoVITS/pull/2662)
+  - İçerik: Varsayılan parti boyutu (batch size) hatasını düzelt
+  - Tür: Düzeltme
+  - Katkıda Bulunan: Spr-Aachen
+
+## 202512
+
+- 2025.12.30 [PR#2703](https://github.com/RVC-Boss/GPT-SoVITS/pull/2703) [PR#2704](https://github.com/RVC-Boss/GPT-SoVITS/pull/2704)
+  - İçerik: Örnekleme (sampling) hatasını düzelt
+  - Tür: Düzeltme
+  - Katkıda Bulunan: ChasonJiang
+
+## 202602
+
+- 2026.02.08 [PR#2727](https://github.com/RVC-Boss/GPT-SoVITS/pull/2727)
+  - İçerik: Kabul edilmeyen Conda koşullarının neden olduğu derleme hatasını düzelt
+  - Tür: Düzeltme
+  - Katkıda Bulunan: Oarora
+- 2026.02.09 [PR#2732](https://github.com/RVC-Boss/GPT-SoVITS/pull/2732)
+  - İçerik: Otomatik ortam kurulumunu optimize et
+  - Tür: Optimizasyon
+  - Katkıda Bulunan: XXXXRT666
+
+# 202604
+
+- 2026.04.18 [PR#2763](https://github.com/RVC-Boss/GPT-SoVITS/pull/2763)
+  - İçerik: Uzun cümlelerde gereksiz hesaplama ve çıkarım yükünü azaltmak için G2PW çıkarım girdi oluşturmayı ve çok sesli harf işlemeyi optimize et
+  - Tür: Optimizasyon
+  - Katkıda Bulunan: baicai-1145
+- 2026.04.18 [PR#2767](https://github.com/RVC-Boss/GPT-SoVITS/pull/2767)
+  - İçerik: Windows altında tek kartta GPT-SoVITS v3 için LoRA eğitim akışını iyileştir
+  - Tür: Optimizasyon
+  - Katkıda Bulunan: 2409324124
+- 2026.04.18 [PR#2755](https://github.com/RVC-Boss/GPT-SoVITS/pull/2755)
+  - İçerik: Birden çok modüldeki çeşitli hataları düzelt
+  - Tür: Düzeltme
+  - Katkıda Bulunan: wishhyt
+- 2026.04.18 [PR#2758](https://github.com/RVC-Boss/GPT-SoVITS/pull/2758)
+  - İçerik: Veri kümesi işleme için hata işleme ipuçları ekle
+  - Tür: Optimizasyon
+  - Katkıda Bulunan: mushroomcowisheggs
+- 2026.04.18 [PR#2753](https://github.com/RVC-Boss/GPT-SoVITS/pull/2753)
+  - İçerik: Paralel çıkarımdaki bazı hataları düzelt
+  - Tür: Düzeltme
+  - Katkıda Bulunan: wishhyt
+- 2026.04.18 [PR#2733](https://github.com/RVC-Boss/GPT-SoVITS/pull/2733)
+  - İçerik: DPO eğitiminin eksik kelime simülasyonunu desteklememe hatasını düzelt
+  - Tür: Düzeltme
+  - Katkıda Bulunan: Mr-Neutr0n
+- 2026.04.18 [Commit#02425ea](https://github.com/RVC-Boss/GPT-SoVITS/commit/02425ea25680c26c700be0bc158756c69103d827)
+  - İçerik: ONNX betiğinde (Optional vb.) eksik içe aktarmaları düzelt
+  - Tür: Düzeltme
+  - Katkıda Bulunan: RVC-Boss
--- a/tools/asr/funasr_asr.py
+++ b/tools/asr/funasr_asr.py
@ -39,6 +39,7 @@ def create_model(language="zh"):
            local_dir="tools/asr/models/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch",
        )
        model_revision = "v2.0.4"
+        vad_model_revision = punc_model_revision = "v2.0.4"
    elif language == "yue":
        path_asr = "tools/asr/models/speech_UniASR_asr_2pass-cantonese-CHS-16k-common-vocab1468-tensorflow1-online"
        snapshot_download(
@ -51,8 +52,6 @@ def create_model(language="zh"):
    else:
        raise ValueError(f"{language} is not supported")

-    vad_model_revision = punc_model_revision = "v2.0.4"
-
    if language in funasr_models:
        return funasr_models[language]
    else:
--- a/tools/uvr5/lib/lib_v5/spec_utils.py
+++ b/tools/uvr5/lib/lib_v5/spec_utils.py
@ -485,6 +485,8 @@ def istft(spec, hl):
    wave_right = librosa.istft(spec_right, hop_length=hl)
    wave = np.asfortranarray([wave_left, wave_right])

+    return wave
+

 if __name__ == "__main__":
    import argparse
Author	SHA1	Message	Date
Jacky He	03631feafd	Merge 485cb85a552c5bd5b6387569da9b1727332e940e into ea2d2a81667239d37615697e8f0056e35bab2db6	2026-04-20 10:05:33 +00:00
RVC-Boss	ea2d2a8166	Update README.md	2026-04-19 21:02:57 +08:00
SapphireLab	d9f03dad3e	Update Documentation (#2768 ) * 调整日志格式 * docs: Update other languages' changelogs	2026-04-18 22:33:55 +08:00
RVC-Boss	647935357a	Update Changelog_CN.md	2026-04-18 19:01:11 +08:00
RVC-Boss	02425ea256	Fixed issues such as missing imports for types like `Optional`. Fixed issues such as missing imports for types like `Optional`.	2026-04-18 17:33:53 +08:00
Harikrishna KP	938f05fce8	fix: correct torch.randint upper bound to include both values (#2733 )	2026-04-18 17:19:55 +08:00
huang yutong	445d18ccce	fix: 修复 TTS 音频后处理中的多个缺陷 (#2753 ) 1. 修复音频超采样时 int16 双重转换导致整数溢出（CRITICAL） - audio_postprocess 中 `audio = (audio * 32768).astype(np.int16)` 位于 if/else 块之外无条件执行，当 super_sampling=True 时音频已在分支内转为 int16，再次乘以 32768 导致溢出和音频完全失真 - 同时修复 super_sampling=True 但超分模型不存在时 torch.Tensor 调用 .astype() 的 AttributeError 2. 修复 batched vocoder 推理中 padding_len=0 导致音频丢失（HIGH） - 当 padding_len 恰好为 0 时，`-0 * upsample_rate == 0`，切片 `audio[x:0]` 返回空张量，导致整段音频丢失 3. 修复文件不存在时错误地抛出 FileExistsError（LOW） - 应为 FileNotFoundError Made-with: Cursor	2026-04-18 17:16:24 +08:00
Mushroomcowisheggs	00ce973412	feat: 添加数据集的错误处理提示 (#2758 ) Co-authored-by: moomushroom <107208254+moomushroom@users.noreply.github.com>	2026-04-18 17:13:30 +08:00
huang yutong	14191901cd	fix: 修复多个模块中的独立 bug (#2755 ) 1. 修复 sync_buffer 中除以函数对象而非调用结果（distrib.py） - `buffer.data /= world_size` 中 world_size 是函数，缺少 ()，导致 TypeError 使分布式训练 buffer 同步失败 2. 修复 istft 函数缺少 return 语句（spec_utils.py） - 函数计算了结果但未返回，调用者始终得到 None 3. 修复 cut0 返回字面量 "/n" 而非换行符 "\n"（text_segmentation_method.py） - 导致后续 text.split("\n") 无法正确切分，字面 /n 被当作文本内容 4. 修复粤语 ASR 的 vad/punc model_revision 被无条件覆盖（funasr_asr.py） - 粤语分支将 vad_model_revision 设为空（因不使用 VAD/标点模型），但 if/else 外的赋值将其覆盖为 "v2.0.4"，传入错误的 revision 参数 Made-with: Cursor	2026-04-18 17:10:56 +08:00
东云	780383d5bd	[codex] Improve Windows single-GPU v3 LoRA training / 改进 Windows 单卡 v3 LoRA 训练流程 (#2767 ) * Improve Windows single-GPU v3 LoRA training * Drop unrelated checkpoint helper change from PR * Tighten PR scope to single-GPU training path fixes	2026-04-18 16:54:26 +08:00
白菜工厂1145号员工	ba8de9b760	优化 G2PW 的推理输入构造与多音字处理流程，减少重复计算，降低长句场景下的推理开销 (#2763 ) * Enhance G2P processing by implementing batch input handling in _g2p function, improving efficiency. Update prepare_onnx_input to utilize caching for tokenization and add optional parameters for character ID mapping and phoneme masks. Refactor G2PWOnnxConverter to streamline model loading and configuration management. * Enhance G2PW model input handling by introducing polyphonic context character support and updating the data preparation method to return additional query IDs. This improves the processing of polyphonic characters in sentences.	2026-04-18 16:52:32 +08:00
Jacky He	485cb85a55	fix: determine whether the filename was input or only path is input	2025-08-12 14:03:15 +08:00
Jacky He	baf61b61d8	fix: wrong args name	2025-08-12 12:06:39 +08:00
Jacky He	7263f02706	feat: add optional params	2025-08-11 11:34:08 +08:00
Jacky He	013ed62a78	chore: add new supported language	2025-08-11 10:51:43 +08:00
Jacky He	035964ae78	refactor: better param input change text_path to text direct input and add model smart selector	2025-08-11 10:33:17 +08:00
Jacky He	5285786b57	fix: when text and word2ph is empty, get_bert_feature will not crash but return an empty tensor	2025-08-09 18:26:25 +08:00