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添加faster-whisper转写工具方法

tools/damo_asr/faster-whisper-asr.py

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+import sys,os,traceback
+dir=sys.argv[1]
+model_name=sys.argv[2]
+# opt_name=dir.split("\\")[-1].split("/")[-1]
+opt_name=os.path.basename(dir)
+
+from faster_whisper import WhisperModel
+
+import torch
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+# model_name="small"
+
+if device == "cuda":
+    model = WhisperModel(model_name, device="cuda", compute_type="float16",download_root="./model_from_whisper",local_files_only=False)
+else:
+    model = WhisperModel(model_name, device="cpu", compute_type="int8",download_root="./model_from_whisper",local_files_only=False)
+
+def make_faster(file_path):
+
+    segments, info = model.transcribe(file_path, beam_size=5)
+    print("Detected language '%s' with probability %f" % (info.language, info.language_probability))
+
+    text_str = ""
+    for segment in segments:
+        text_str += f"{segment.text.lstrip()},"
+    
+    print(text_str)
+
+    return info.language,text_str.rstrip(",")
+
+opt=[]
+for name in os.listdir(dir):
+    try:
+        res = make_faster("%s/%s"%(dir,name))
+        text = res[1]
+        opt.append("%s/%s|%s|%s|%s"%(dir,name,opt_name,res[0],text))
+    except:
+        print(traceback.format_exc())
+
+opt_dir="output/asr_opt"
+os.makedirs(opt_dir,exist_ok=True)
+with open("%s/%s.list"%(opt_dir,"slicer_opt"),"w",encoding="utf-8")as f:f.write("\n".join(opt))