Upload WhisperApp.py

WhisperApp.py

@@ -0,0 +1,34 @@
+import whisper
+import gradio as gr
+import time
+
+def transcribe(audio):
+
+    #time.sleep(3)
+    # load audio and pad/trim it to fit 30 seconds
+    audio = whisper.load_audio(audio)
+    audio = whisper.pad_or_trim(audio)
+
+    # make log-Mel spectrogram and move to the same device as the model
+    mel = whisper.log_mel_spectrogram(audio).to(model.device)
+
+    # detect the spoken language
+    _, probs = model.detect_language(mel)
+    print(f"Detected language: {max(probs, key=probs.get)}")
+
+    # decode the audio
+    options = whisper.DecodingOptions()
+    result = whisper.decode(model, mel, options)
+    return result.text
+
+
+gr.Interface(
+    title = 'OpenAI-Whisper Audio to Text Web UI',
+    fn=transcribe,
+    inputs=[
+        gr.inputs.Audio(type="filepath")
+    ],
+    outputs=[
+        "textbox"
+    ],
+    live=True).launch()