Update app.py

app.py

@@ -8,15 +8,15 @@ title = "Transcribe speech in several languages"
 device = "cuda:0" if torch.cuda.is_available() else "cpu"
 
 asr_pipe_audio2Text_Ge = pipeline(task="automatic-speech-recognition", model="jonatasgrosman/wav2vec2-large-xlsr-53-german")
-asr_pipe_whisper = pipeline(task="automatic-speech-recognition", model="openai/whisper-base", device=device)
+asr_pipe_whisper = pipeline(task="automatic-speech-recognition", model="openai/whisper-medium", device=device)
 
 def transcribeFile(inputlang, audio_path : str) -> str:
     #transcription = asr_pipe_audio2Text_Ge(audio_path)
     #transcription = asr_pipe_whisper(audio_path, max_new_tokens=256, generate_kwargs={"task":"transcribe"})
     if inputlang == "Auto Detect":
-        transcription = asr_pipe_whisper(audio_path, chunk_length_s=25, stride_length_s=(5, 0), generate_kwargs={"task":"transcribe"})
+        transcription = asr_pipe_whisper(audio_path, chunk_length_s=25, stride_length_s=(5, 5), generate_kwargs={"task":"transcribe"})
     elif inputlang == "German":
-        transcription = asr_pipe_audio2Text_Ge(audio_path, chunk_length_s=25, stride_length_s=(5, 0))    
+        transcription = asr_pipe_audio2Text_Ge(audio_path, chunk_length_s=25, stride_length_s=(5, 5))    
     return transcription["text"]
 
 def translateAudio(audio_path):