Spaces:
Running
Running
| import os | |
| import gradio as gr | |
| from transformers import pipeline | |
| title = "Transcribe speech several languages" | |
| pipelineGE = pipeline(task="automatic-speech-recognition", model="jonatasgrosman/wav2vec2-large-xlsr-53-german") | |
| pipelineEN = pipeline(task="automatic-speech-recognition", model="openai/whisper-large") | |
| def transcribeFile(audio_path : str) -> str: | |
| transcription = pipelineGE(audio_path) | |
| return transcription["text"] | |
| def transcribeFileMulti(inputlang, audio_path : str) -> str: | |
| if inputlang == "English": | |
| transcription = pipelineEN(audio_path) | |
| elif inputlang == "German": | |
| transcription = pipelineGE(audio_path) | |
| return transcription["text"] | |
| app1 = gr.Interface( | |
| fn=transcribeFile, | |
| inputs=gr.inputs.Audio(label="Upload audio file", type="filepath"), | |
| 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() | |