Update app.py

app.py

@@ -4,7 +4,7 @@ import torch
 from transformers import pipeline
 
 
-title = "Transcribe speech several languages"
+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")
@@ -14,9 +14,9 @@ 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 == "English":
-        transcription = asr_pipe_whisper(audio_path, chunk_length_s=10, stride_length_s=(4, 2))
+        transcription = asr_pipe_whisper(audio_path, chunk_length_s=25, stride_length_s=(5, 0), generate_kwargs={"task":"transcribe"})
     elif inputlang == "German":
-        transcription = asr_pipe_audio2Text_Ge(audio_path, chunk_length_s=10, stride_length_s=(4, 2))    
+        transcription = asr_pipe_audio2Text_Ge(audio_path, chunk_length_s=25, stride_length_s=(5, 0))    
     return transcription["text"]
 
 def translateAudio(audio_path):