Merge dbeacf51dc079446a509ebbb1ff89dfe557395a5 into 08d627c3338173c3229286d8787060d6559fe0f8

requirements.txt

@@ -10,7 +10,7 @@ ffmpeg-python
 onnxruntime; platform_machine == "aarch64" or platform_machine == "arm64"
 onnxruntime-gpu; platform_machine == "x86_64" or platform_machine == "AMD64"
 tqdm
-funasr==1.0.27
+funasr>=1.3.7
 cn2an
 pypinyin
 pyopenjtalk>=0.4.1

tools/asr/config.py

@@ -5,15 +5,14 @@ def get_models():
         "large-v2",
         "large-v3",
         "large-v3-turbo",
-        #"distil-large-v2",
-        #"distil-large-v3",
-        #"distil-large-v3.5",
     ]
     return model_size_list
 
 
 asr_dict = {
-    "达摩 ASR (中文)": {"lang": ["zh", "yue"], "size": ["large"], "path": "funasr_asr.py", "precision": ["float32"]},
+    "Fun-ASR-Nano (31语种+方言, 推荐)": {"lang": ["zh", "en", "ja", "ko", "yue", "auto"], "size": ["large"], "path": "funasr_asr.py", "precision": ["float32"]},
+    "SenseVoice (极速, 5语种)": {"lang": ["zh", "en", "ja", "ko", "yue", "auto"], "size": ["large"], "path": "funasr_asr.py", "precision": ["float32"]},
+    "达摩 ASR (中文经典)": {"lang": ["zh", "yue"], "size": ["large"], "path": "funasr_asr.py", "precision": ["float32"]},
     "Faster Whisper (多语种)": {
         "lang": ["auto", "en", "ja", "ko"],
         "size": get_models(),

tools/asr/funasr_asr.py

@@ -11,9 +11,9 @@ from tqdm import tqdm
 funasr_models = {}  # 存储模型避免重复加载
 
 
-def only_asr(input_file, language):
+def only_asr(input_file, language, backend="fun-asr-nano"):
     try:
-        model = create_model(language)
+        model = create_model(language, backend=backend)
         text = model.generate(input=input_file)[0]["text"]
     except Exception:
         text = ""
@@ -21,7 +21,39 @@ def only_asr(input_file, language):
     return text
 
 
-def create_model(language="zh"):
+def create_model(language="zh", **kwargs):
+    backend = kwargs.get("backend", "fun-asr-nano")
+
+    # For non-classic backends, route to multilingual models regardless of language
+    if backend in ("fun-asr-nano", "sensevoice") and language != "yue":
+        import torch
+        device = "cuda" if torch.cuda.is_available() else "cpu"
+        cache_key = f"{language}_{backend}"
+        if cache_key in funasr_models:
+            return funasr_models[cache_key]
+
+        if backend == "fun-asr-nano":
+            model = AutoModel(
+                model="FunAudioLLM/Fun-ASR-Nano-2512",
+                trust_remote_code=True,
+                hub="hf",
+                vad_model="fsmn-vad",
+                device=device,
+                disable_update=True,
+            )
+            print(f"FunASR Fun-ASR-Nano 模型加载完成: {language.upper()}")
+        else:
+            model = AutoModel(
+                model="iic/SenseVoiceSmall",
+                vad_model="fsmn-vad",
+                device=device,
+                disable_update=True,
+            )
+            print(f"FunASR SenseVoice 模型加载完成: {language.upper()}")
+
+        funasr_models[cache_key] = model
+        return model
+
     if language == "zh":
         path_vad = "tools/asr/models/speech_fsmn_vad_zh-cn-16k-common-pytorch"
         path_punc = "tools/asr/models/punc_ct-transformer_zh-cn-common-vocab272727-pytorch"
@@ -50,7 +82,7 @@ def create_model(language="zh"):
         vad_model_revision = punc_model_revision = ""
         model_revision = "master"
     else:
-        raise ValueError(f"{language} is not supported")
+        raise ValueError(f"{language} is not supported. Supported: zh, yue, ja, en, ko, auto")
 
     if language in funasr_models:
         return funasr_models[language]
@@ -69,14 +101,14 @@ def create_model(language="zh"):
         return model
 
 
-def execute_asr(input_folder, output_folder, model_size, language):
+def execute_asr(input_folder, output_folder, model_size, language, backend="fun-asr-nano"):
     input_file_names = os.listdir(input_folder)
     input_file_names.sort()
 
     output = []
     output_file_name = os.path.basename(input_folder)
 
-    model = create_model(language)
+    model = create_model(language, backend=backend)
 
     for file_name in tqdm(input_file_names):
         try:
@@ -105,7 +137,7 @@ if __name__ == "__main__":
     parser.add_argument("-o", "--output_folder", type=str, required=True, help="Output folder to store transcriptions.")
     parser.add_argument("-s", "--model_size", type=str, default="large", help="Model Size of FunASR is Large")
     parser.add_argument(
-        "-l", "--language", type=str, default="zh", choices=["zh", "yue", "auto"], help="Language of the audio files."
+        "-l", "--language", type=str, default="zh", choices=["zh", "yue", "ja", "en", "ko", "auto"], help="Language of the audio files."
     )
     parser.add_argument(
         "-p", "--precision", type=str, default="float16", choices=["float16", "float32"], help="fp16 or fp32"