| import gradio as gr | |
| import whisper | |
| MODEL = whisper.load_model("small.en") | |
| def transcribe(audio): | |
| result = MODEL.transcribe(audio) | |
| try: | |
| return result["text"] | |
| except: | |
| return "" | |
| examples = [["apollo11_example.mp3"], ["ariane6_example.mp3"]] | |
| ui = gr.Interface( | |
| fn=transcribe, | |
| inputs=gr.Audio( | |
| sources=["microphone", "upload"], | |
| type="filepath", | |
| label="Input Audio", | |
| ), | |
| outputs=gr.Textbox( | |
| label="Transcription", | |
| placeholder="The transcribed text will appear here...", | |
| ), | |
| title="ECHO", | |
| description=""" | |
| This is a demo of the transcription capabilities of "ECHO". This could be adapded to run real-time transcription on a live audio stream like ISS communications. | |
| ### How to use: | |
| 1. **Record or Upload**: Click on the microphone icon 🎙️ to record audio, usign your microphone, or click on the upload button ⬆️ to upload an audio file. | |
| You can also use the **Examples** provided below, as inputs, by clicking on them. | |
| 2. **Click Submit**: Clicking the submit button will transcribe the audio. | |
| 3. **Read the Transcription**: The transcribed text will appear in the text box below the audio input section. | |
| """, | |
| examples=examples, | |
| ) | |
| ui.launch() | |