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import os
import gradio as gr
import torch
from transformers import pipeline
title = "Transcribe speech in several languages"
device = "cuda:0" if torch.cuda.is_available() else "cpu"
asr_pipe_audio2Text_Ge = pipeline(task="automatic-speech-recognition", model="jonatasgrosman/wav2vec2-large-xlsr-53-german")
asr_pipe_whisper = pipeline(task="automatic-speech-recognition", model="openai/whisper-base", device=device)
def transcribeFile(inputlang, audio_path : str) -> str:
#transcription = asr_pipe_audio2Text_Ge(audio_path)
#transcription = asr_pipe_whisper(audio_path, max_new_tokens=256, generate_kwargs={"task":"transcribe"})
if inputlang == "English":
transcription = asr_pipe_whisper(audio_path, chunk_length_s=25, stride_length_s=(5, 0), generate_kwargs={"task":"transcribe"})
elif inputlang == "German":
transcription = asr_pipe_audio2Text_Ge(audio_path, chunk_length_s=25, stride_length_s=(5, 0))
return transcription["text"]
def translateAudio(audio_path):
translationOutput = asr_pipe_whisper(audio_path, max_new_tokens=256, generate_kwargs={"task":"translate"})
return translationOutput
def transcribeFileMulti(inputlang, audio_path : str) -> str:
if inputlang == "English":
transcription = asr_pipe_whisper(audio_path)
elif inputlang == "German":
transcription = asr_pipe_audio2Text_Ge(audio_path)
translation = translateAudio(audio_path)
t1 = transcription["text"]
t2 = translation["text"]
output = t1+t2
return output #transcription["text"]
app1 = gr.Interface(
fn=transcribeFile,
#inputs=gr.inputs.Audio(label="Upload audio file", type="filepath"),
inputs=[gr.Radio(["English", "German"], value="German", label="Source Language", info="Select the language of the speech you want to transcribe"),
gr.Audio(source="upload", type="filepath",label="Upload audio file")],
outputs="text",
title=title
)
app2 = gr.Interface(
fn=transcribeFileMulti,
inputs=[gr.Radio(["English", "German"], value="German", label="Source Language", info="Select the language of the speech you want to transcribe"),
gr.Audio(source="microphone", type="filepath")],
outputs="text",
title=title
)
demo = gr.TabbedInterface([app1, app2], ["Audio File", "Microphone"])
if __name__ == "__main__":
demo.launch()
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