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modules/speech_recognition/whisper_module.py

@@ -14,23 +14,21 @@ References:
 """
 from flask import jsonify, abort, request
 
-import whisper
+from faster_whisper import WhisperModel
 
 DEBUG_PREFIX = "<stt whisper module>"
 RECORDING_FILE_PATH = "stt_test.wav"
 
-model = None
+model_size = "large-v3-turbo"
+
+model = WhisperModel(model_size, device="cuda", compute_type="float16")
 
 def load_model(file_path=None):
     """
     Load given vosk model from file or default to en-us model.
     Download model to user cache folder, example: C:/Users/toto/.cache/vosk
     """
-
-    if file_path is None:
-        return whisper.load_model("base.en")
-    else:
-        return whisper.load_model(file_path)
+    return WhisperModel(model_size, device="cuda", compute_type="float16")
 
 def process_audio():
     """
@@ -39,15 +37,16 @@ def process_audio():
 
     if model is None:
         print(DEBUG_PREFIX,"Whisper model not initialized yet.")
-        return ""
+        return WhisperModel(model_size, device="cuda", compute_type="float16")
 
     try:
         file = request.files.get('AudioFile')
         language = request.form.get('language', default=None)
         file.save(RECORDING_FILE_PATH)
-
-        result = model.transcribe(RECORDING_FILE_PATH, condition_on_previous_text=False, language=language)
-        transcript = result["text"]
+        segments, info = model.transcribe(RECORDING_FILE_PATH, beam_size=5)
+        transcript=""
+        for segment in segments:
+            transcript=transcript+" "+segment.text
         print(DEBUG_PREFIX, "Transcripted from audio file (whisper):", transcript)
 
         return jsonify({"transcript": transcript})