Update app.py

app.py

@@ -21,17 +21,16 @@ genders = sorted(set(entry["gender"] for entry in data))
 accents = sorted(set(entry["accent"] for entry in data))
 
 # Load ASR pipelines
-device = 0 if torch.cuda.is_available() else -1
-pipe_whisper_tiny = pipeline("automatic-speech-recognition", model="openai/whisper-tiny", device=device)
-pipe_whisper_tiny_en = pipeline("automatic-speech-recognition", model="openai/whisper-tiny.en", device=device)
-pipe_whisper_base = pipeline("automatic-speech-recognition", model="openai/whisper-base", device=device)
-pipe_whisper_base_en = pipeline("automatic-speech-recognition", model="openai/whisper-base.en", device=device)
-pipe_whisper_medium = pipeline("automatic-speech-recognition", model="openai/whisper-medium", device=device)
-pipe_whisper_medium_en = pipeline("automatic-speech-recognition", model="openai/whisper-medium.en", device=device)
-pipe_distil_whisper_large = pipeline("automatic-speech-recognition", model="distil-whisper/distil-large-v3.5", device=device)
-pipe_wav2vec2_base_960h = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-base-960h", device=device)
-pipe_wav2vec2_large_960h = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-large-960h", device=device)
-pipe_hubert_large_ls960_ft = pipeline("automatic-speech-recognition", model="facebook/hubert-large-ls960-ft", device=device)
+pipe_whisper_tiny = pipeline("automatic-speech-recognition", model="openai/whisper-tiny")
+pipe_whisper_tiny_en = pipeline("automatic-speech-recognition", model="openai/whisper-tiny.en")
+pipe_whisper_base = pipeline("automatic-speech-recognition", model="openai/whisper-base")
+pipe_whisper_base_en = pipeline("automatic-speech-recognition", model="openai/whisper-base.en")
+pipe_whisper_medium = pipeline("automatic-speech-recognition", model="openai/whisper-medium")
+pipe_whisper_medium_en = pipeline("automatic-speech-recognition", model="openai/whisper-medium.en")
+pipe_distil_whisper_large = pipeline("automatic-speech-recognition", model="distil-whisper/distil-large-v3.5")
+pipe_wav2vec2_base_960h = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-base-960h")
+pipe_wav2vec2_large_960h = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-large-960h")
+pipe_hubert_large_ls960_ft = pipeline("automatic-speech-recognition", model="facebook/hubert-large-ls960-ft")
 
 # Functions
 def convert_to_wav(file_path):