File size: 747 Bytes
ed71812
 
 
 
 
d0d0cf3
ed71812
 
 
 
 
d0d0cf3
ed71812
 
d0d0cf3
ed71812
 
 
45853c5
ed71812
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
import gradio as gr
from transformers import pipeline
import spaces

# Load the Whisper model from Hugging Face
model = pipeline("automatic-speech-recognition", model="ylacombe/whisper-large-v3-turbo", chunk_length_s=30, device=0)

# Function to process audio input and transcribe it
@spaces.GPU
def transcribe(audio):
    # Load and preprocess the audio
    transcription = model(audio,batch_size=1000, generate_kwargs={"task": "transcribe"}, return_timestamps=True)["text"]
    return transcription


# Gradio interface
interface = gr.Interface(
    fn=transcribe, 
    inputs=gr.Audio(sources="microphone", type="filepath"),  
    outputs="text",
    title="Whisper Voice Transcription with Hugging Face"
)

# Launch the app
interface.launch()