Spaces:
Runtime error
Runtime error
File size: 1,647 Bytes
61a93bc |
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 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 |
import gradio as gr
import soundfile as sf
import numpy as np
import tempfile
import torchaudio
from transformers import AutoModel
# Load ASR Model
def load_model():
return AutoModel.from_pretrained("ai4bharat/indic-conformer-600m-multilingual", trust_remote_code=True)
model = load_model()
def process_audio(audio, language, decoding_method):
if isinstance(audio, tuple): # Recorded audio
sample_rate, data = audio
temp_wav = tempfile.NamedTemporaryFile(delete=False, suffix=".wav")
sf.write(temp_wav.name, data, sample_rate)
audio_path = temp_wav.name
else: # Uploaded file
audio_path = audio
# Load and resample audio
wav, sr = torchaudio.load(audio_path)
target_sample_rate = 16000
if sr != target_sample_rate:
resampler = torchaudio.transforms.Resample(orig_freq=sr, new_freq=target_sample_rate)
wav = resampler(wav)
# Perform ASR with selected decoding method
transcription = model(wav, language, decoding_method)
return transcription
iface = gr.Interface(
fn=process_audio,
inputs=[
gr.Audio(source="microphone", type="numpy"),
gr.Audio(source="upload"),
gr.Dropdown(["hi", "ta", "bn", "mr", "te", "gu", "kn", "ml", "pa", "ur"], label="Select Language"),
gr.Radio(["ctc", "rnnt"], label="Decoding Method")
],
outputs="text",
title="Multilingual ASR with Indic-Conformer",
description="Record or upload an audio file, select a language and decoding method, and transcribe it using the AI4Bharat Indic-Conformer model."
)
if __name__ == "__main__":
iface.launch()
|