audio transcriber

Initial demo release of Microsoft Teams meeting recording transcriber using Gradio.

This demo is powered by 🤗's ASR models, primarily Whisper by OpenAI.
Optimisations are developed by Vaibhavs10/insanely-fast-whisper.

transcriberUI.py

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+import gradio as gr
+import time
+import os
+from pydub import AudioSegment
+
+def audio_converter(audio_file:str):
+    audio_input = AudioSegment.from_file(audio_file,'m4a')
+    audio_input_name = os.path.splitext(audio_file)[0]
+    audio_wav_filename = f"{audio_input_name}.wav"
+    audio_input.export(audio_wav_filename, 'wav')
+    
+    return audio_wav_filename
+
+def asr_transcriber(audio_file):
+    from transformers import pipeline
+    import torch
+    import random
+
+    audio_file_wav = audio_converter(audio_file)
+
+    device_id = "mps"
+    flash = False
+   
+    # Initialize the ASR pipeline
+    pipe = pipeline(
+        "automatic-speech-recognition",
+        model="openai/whisper-large-v3",
+        torch_dtype=torch.float16,
+        device=device_id
+    )
+    if device_id == "mps":
+            torch.mps.empty_cache()
+    elif not flash:
+        pipe.model = pipe.model.to_bettertransformer()
+        
+    ts = True
+    language = None
+    task = "transcribe"
+
+    json_output = pipe(
+        audio_file_wav, 
+        chunk_length_s=30, 
+        batch_size=2, 
+        generate_kwargs={"task": task, "language": language},
+        return_timestamps=ts
+    )
+
+    return json_output["text"]
+
+with gr.Blocks() as transcriberUI:
+    gr.Markdown(
+    """
+    # Ola Xara & Solange!
+    Clicar no botao abaixo para selecionar o Audio a ser transcrito!
+    Ambiente de Teste: pode demorar um pouco. Nao fiquem nervosos :-)
+    """)
+    inp = gr.File(label="Arquivo de Audio", show_label=True, file_count="single", file_types=["m4a"])
+    transcribe = gr.Textbox(label="Transcricao", show_label=True, show_copy_button=True)
+    inp.upload(asr_transcriber, inp, transcribe)
+
+transcriberUI.launch(share=True)