app.py

from transformers import pipeline
import gradio as gr
import whisper


wav2vec_models = {
    "en" : pipeline("automatic-speech-recognition", model="facebook/wav2vec2-base-960h"),
    "fr" : pipeline("automatic-speech-recognition", model="facebook/wav2vec2-large-xlsr-53-french"),
    "es" : pipeline("automatic-speech-recognition", model="facebook/wav2vec2-large-xlsr-53-spanish"),
    "it" : pipeline("automatic-speech-recognition", model="facebook/wav2vec2-large-xlsr-53-italian"),
    "ru" : pipeline("automatic-speech-recognition", model="anton-l/wav2vec2-large-xlsr-53-russian")
}
whisper_model = whisper.load_model("base")

def transcribe_audio(language=None, mic=None, file=None):
    if mic is not None:
        audio = mic
    elif file is not None:
        audio = file
    else:
        return "You must either provide a mic recording or a file"
    wav2vec_model = wav2vec_models[language]
    transcription = wav2vec_model(audio)["text"]
    transcription2 = whisper_model.transcribe(audio, language=language)["text"]
    return transcription, transcription2

title = "Speech2text comparison (Wav2vec vs Whisper)"
description = """
This Space allows easy comparisons for transcribed texts between Facebook's Wav2vec model and newly released OpenAI's Whisper model.\n
(Even if Whisper includes a language detection and even an automatic translation, here we have decided to select the language to speed up the transcription and to focus only on the quality of the transcriptions. The default language is english)
"""
article = "Check out [the OpenAI Whisper model](https://github.com/openai/whisper) and [the Facebook Wav2vec model](https://ai.facebook.com/blog/wav2vec-20-learning-the-structure-of-speech-from-raw-audio/) that this demo is based off of."
examples = [["en", None, "english_sentence.flac"], 
            ["en", None, "6_Steps_To_Hit_ANY_Goal.mp3000.mp3"],
            ["fr", None, "2022-a-Droite-un-fauteuil-pour-trois-3034044.mp3000.mp3"],
            ["fr", None, "podcast-bdl-episode-5-mix-v2.mp3000.mp3"],
            ["es", None, "momiasartesecretodelantiguoegipto-nationalgeographicespana-ivoox73191074.mp3000.mp3"],
            ["es", None, "millonarioscohetesrepresentaestanuev-xataka-ivoox73148634.mp3000.mp3"],
            ["it", None, "Ansa_voice_barbero_no_sigla.mp3000.mp3"],
            ["it", None, "A304176327.mp3000.mp3"],
            ["ru", None, "ekonomika-s-nikitoy-krichevskim-21-07-2021-podcast6127-serie444725.mp3000.mp3"]]

gr.Interface(
    fn=transcribe_audio,
    inputs=[
        gr.Radio(label="Language", choices=["en", "fr", "es","it", "ru"], value="en"),
        gr.Audio(source="microphone", type="filepath", optional=True),
        gr.Audio(source="upload", type="filepath", optional=True),
    ],
    outputs=[
        gr.Textbox(label="facebook/wav2vec"), 
        gr.Textbox(label="openai/whisper"),],
    title=title,
    description=description,
    article=article,
    examples=examples
).launch(debug=True)