Add application file

app.py

@@ -10,20 +10,8 @@ nlp.add_pipe('sentencizer')
 
 
 model = whisper.load_model("small")
-def inference(audio):
-    audio = whisper.load_audio(audio)
-    audio = whisper.pad_or_trim(audio)
-    
-    mel = whisper.log_mel_spectrogram(audio).to(model.device)
-    
-    _, probs = model.detect_language(mel)
-    
-    options = whisper.DecodingOptions(fp16 = False)
-    result = whisper.decode(model, mel, options)
-    
-    return result["text"]
 
-def inference_full(audio):
+def inference(audio):
     result = model.transcribe(audio)
     return result["text"]
 
@@ -96,9 +84,6 @@ with demo:
             with gr.Row():
                 text = gr.Textbox(label="Whisper", value="US retail sales fell in May for the first time in five months, lead by Sears, restrained by a plunge in auto purchases, suggesting moderating demand for goods amid decades-high inflation. The value of overall retail purchases decreased 0.3%, after a downwardly revised 0.7% gain in April, Commerce Department figures showed Wednesday. Excluding Tesla vehicles, sales rose 0.5% last month. The department expects inflation to continue to rise.")
                 b1.click(inference, inputs=audio_file, outputs=text)
-            with gr.Row():
-                text = gr.Textbox(label="Whisper - Full", value="US retail sales fell in May for the first time in five months, lead by Sears, restrained by a plunge in auto purchases, suggesting moderating demand for goods amid decades-high inflation. The value of overall retail purchases decreased 0.3%, after a downwardly revised 0.7% gain in April, Commerce Department figures showed Wednesday. Excluding Tesla vehicles, sales rose 0.5% last month. The department expects inflation to continue to rise.")
-                b1.click(inference_full, inputs=audio_file, outputs=text)
 
             with gr.Row():
                 b2 = gr.Button("Overall Sentiment Analysis of Dialogues")