添加非中文语言的asr操作

Ref_Audio_Selector/file/test_content/test_content.txt

@@ -10,3 +10,4 @@
 并且在这个眼镜中设置一个转换系统，将接收到的背景辐射的波长压缩七个数量级，将7厘米波转换成红光。
 这样，观众在夜里戴上这种眼镜，就能亲眼看到宇宙的特制背景辐射，现在，也能看到宇宙闪烁。
 这东西现在哪儿？能告诉我吗
+希望各位猫猫给视频三连支持一下猫窝，十分感谢支持喵~

Ref_Audio_Selector/ref_audio_selector_webui.py

@@ -515,6 +515,12 @@ def delete_ref_audio_below_boundary(ref_audio_path, text_text_similarity_result_
         text_delete_ref_audio_below_boundary_info = f"发生异常：{e}"
     return text_delete_ref_audio_below_boundary_info
 
+def change_lang_choices(key): #根据选择的模型修改可选的语言
+    # return gr.Dropdown(choices=asr_dict[key]['lang'])
+    return {"__type__": "update", "choices": asr_dict[key]['lang'],"value":asr_dict[key]['lang'][0]}
+def change_size_choices(key): # 根据选择的模型修改可选的模型尺寸
+    # return gr.Dropdown(choices=asr_dict[key]['size'])
+    return {"__type__": "update", "choices": asr_dict[key]['size']}
 
 
 def save_generate_audio_url(generate_audio_url):
@@ -687,7 +693,10 @@ if __name__ == '__main__':
             text_emotion.blur(save_emotion_param, [text_emotion], [])
             gr.Markdown(value=i18n("2.3：配置待推理文本，一句一行，不要太多，10条即可"))
             default_test_content_path = params.default_test_text_path
-            text_test_content = gr.Text(label=i18n("请输入待推理文本路径"), value=default_test_content_path)
+            with gr.Row():
+                text_test_content = gr.Text(label=i18n("请输入待推理文本路径"), value=default_test_content_path)
+                button_open_test_content_file = gr.Button(i18n("打开待推理文本文件"), variant="primary")
+                button_open_test_content_file.click(open_file, [text_test_content], [])
             gr.Markdown(value=i18n("2.4：开始批量推理，这个过程比较耗时，可以去干点别的"))
             slider_request_concurrency_num = gr.Slider(minimum=1, maximum=10, step=1, label=i18n("请输入请求并发数，会根据此数创建对应数量的子进程并行发起推理请求"), value=3,
                       interactive=True)
@@ -703,7 +712,7 @@ if __name__ == '__main__':
             with gr.Row():
                 dropdown_asr_model = gr.Dropdown(
                     label=i18n("ASR 模型"),
-                    choices=[],
+                    choices=list(asr_dict.keys()),
                     interactive=True,
                     value="达摩 ASR (中文)"
                 )
@@ -719,6 +728,8 @@ if __name__ == '__main__':
                     interactive=True,
                     value="zh"
                 )
+                dropdown_asr_model.change(change_lang_choices, [dropdown_asr_model], [dropdown_asr_lang])
+                dropdown_asr_model.change(change_size_choices, [dropdown_asr_model], [dropdown_asr_size])
             with gr.Row():
                 button_asr = gr.Button(i18n("启动asr"), variant="primary")
                 text_asr_info = gr.Text(label=i18n("asr结果"), value="", interactive=False)

Ref_Audio_Selector/tool/asr/fasterwhisper_asr_multi_level_dir.py

@@ -0,0 +1,119 @@
+import argparse
+import os
+import traceback
+import Ref_Audio_Selector.config_param.config_params as params
+
+os.environ["HF_ENDPOINT"] = "https://hf-mirror.com"
+os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"
+
+import torch
+from faster_whisper import WhisperModel
+from tqdm import tqdm
+
+from tools.asr.config import check_fw_local_models
+from Ref_Audio_Selector.config_param.log_config import logger
+
+language_code_list = [
+    "af", "am", "ar", "as", "az",
+    "ba", "be", "bg", "bn", "bo",
+    "br", "bs", "ca", "cs", "cy",
+    "da", "de", "el", "en", "es",
+    "et", "eu", "fa", "fi", "fo",
+    "fr", "gl", "gu", "ha", "haw",
+    "he", "hi", "hr", "ht", "hu",
+    "hy", "id", "is", "it", "ja",
+    "jw", "ka", "kk", "km", "kn",
+    "ko", "la", "lb", "ln", "lo",
+    "lt", "lv", "mg", "mi", "mk",
+    "ml", "mn", "mr", "ms", "mt",
+    "my", "ne", "nl", "nn", "no",
+    "oc", "pa", "pl", "ps", "pt",
+    "ro", "ru", "sa", "sd", "si",
+    "sk", "sl", "sn", "so", "sq",
+    "sr", "su", "sv", "sw", "ta",
+    "te", "tg", "th", "tk", "tl",
+    "tr", "tt", "uk", "ur", "uz",
+    "vi", "yi", "yo", "zh", "yue",
+    "auto"]
+
+
+def execute_asr_multi_level_dir(input_folder, output_folder, model_size, language, precision):
+    if '-local' in model_size:
+        model_size = model_size[:-6]
+        model_path = f'tools/asr/models/faster-whisper-{model_size}'
+    else:
+        model_path = model_size
+    if language == 'auto':
+        language = None  # 不设置语种由模型自动输出概率最高的语种
+    logger.info("loading faster whisper model:", model_size, model_path)
+    device = 'cuda' if torch.cuda.is_available() else 'cpu'
+    try:
+        model = WhisperModel(model_path, device=device, compute_type=precision)
+    except:
+        return logger.error(traceback.format_exc())
+
+    output = []
+
+    # 递归遍历输入目录及所有子目录
+    for root, dirs, files in os.walk(input_folder):
+        for file_name in sorted(files):
+            # 只处理wav文件（假设是wav文件）
+            if file_name.endswith(".wav"):
+                try:
+                    file_path = os.path.join(input_folder, file_name)
+                    original_text = os.path.basename(root)
+                    segments, info = model.transcribe(
+                        audio=file_path,
+                        beam_size=5,
+                        vad_filter=True,
+                        vad_parameters=dict(min_silence_duration_ms=700),
+                        language=language)
+                    text = ''
+
+                    if info.language == "zh":
+                        logger.info("检测为中文文本, 转 FunASR 处理")
+                        if ("only_asr" not in globals()):
+                            from Ref_Audio_Selector.tool.asr.funasr_asr_multi_level_dir import \
+                                only_asr  # #如果用英文就不需要导入下载模型
+                        text = only_asr(file_path)
+
+                    if text == '':
+                        for segment in segments:
+                            text += segment.text
+                    output.append(f"{file_path}|{original_text}|{info.language.upper()}|{text}")
+                except:
+                    return logger.error(traceback.format_exc())
+
+    output_folder = output_folder
+    os.makedirs(output_folder, exist_ok=True)
+    output_file_path = os.path.abspath(f'{output_folder}/{params.asr_filename}.list')
+
+    with open(output_file_path, "w", encoding="utf-8") as f:
+        f.write("\n".join(output))
+        logger.info(f"ASR 任务完成->标注文件路径: {output_file_path}\n")
+    return output_file_path
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument("-i", "--input_folder", type=str, required=True,
+                        help="Path to the folder containing WAV files.")
+    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-v3',
+                        choices=check_fw_local_models(),
+                        help="Model Size of Faster Whisper")
+    parser.add_argument("-l", "--language", type=str, default='ja',
+                        choices=language_code_list,
+                        help="Language of the audio files.")
+    parser.add_argument("-p", "--precision", type=str, default='float16', choices=['float16', 'float32'],
+                        help="fp16 or fp32")
+
+    cmd = parser.parse_args()
+    output_file_path = execute_asr_multi_level_dir(
+        input_folder=cmd.input_folder,
+        output_folder=cmd.output_folder,
+        model_size=cmd.model_size,
+        language=cmd.language,
+        precision=cmd.precision,
+    )

Ref_Audio_Selector/tool/asr/funasr_asr_multi_level_dir.py

@@ -39,7 +39,6 @@ def only_asr(input_file):
 @timeit_decorator
 def execute_asr_multi_level_dir(input_folder, output_folder, model_size, language):
     output = []
-    output_file_name = os.path.basename(input_folder)
     # 递归遍历输入目录及所有子目录
     for root, dirs, files in os.walk(input_folder):
         for name in sorted(files):
@@ -58,7 +57,7 @@ def execute_asr_multi_level_dir(input_folder, output_folder, model_size, languag
                     logger.error(traceback.format_exc())
 
     # 创建或打开指定的输出目录
-    output_folder = output_folder or "output/asr_opt"
+    output_folder = output_folder
     output_dir_abs = os.path.abspath(output_folder)
     os.makedirs(output_dir_abs, exist_ok=True)