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import gradio as gr
import nemo.collections.asr as nemo_asr
import numpy as np
# Load the pre-trained Kabyle ASR model
asr_model = nemo_asr.models.EncDecRNNTBPEModel.from_pretrained("nvidia/stt_kab_conformer_transducer_large")
# Function to transcribe the audio input
def transcribe(audio):
# Extract audio data and sample rate
audio_data, sample_rate = audio
# Convert audio data to numpy array if it's not already
if isinstance(audio_data, np.ndarray):
audio_data = np.array(audio_data)
# Transcribe the audio
return asr_model.transcribe([audio_data])
# Create the Gradio interface with audio input and text output
iface = gr.Interface(fn=transcribe, inputs="audio", outputs="text")
# Launch the Gradio interface
iface.launch()
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