| import nemo.collections.asr as nemo_asr | |
| import gradio as gr | |
| def transcribe(state, file): | |
| if not audio: | |
| return {state_var: state, transcription_var: state} | |
| asr_model = nemo_asr.models.EncDecCTCModelBPE.from_pretrained(model_name="stt_rw_conformer_ctc_large") | |
| transcription= asr_model.transcribe([audio]) | |
| print(transcription) | |
| return transcription[0] | |
| with gr.Blocks() as demo: | |
| state_var = gr.State("") | |
| with gr.Row(): | |
| with gr.Column(): | |
| uploaded_audio = gr.Audio(label="Upload Audio File", type="filepath") | |
| with gr.Column(): | |
| transcription_var = gr.Textbox(type="text", label="Transcription") | |
| with gr.Row(): | |
| transcribe_button = gr.Button("Transcribe") | |
| transcribe_button.click( | |
| transcribe, | |
| [uploaded_audio], | |
| ) | |
| demo.launch() |