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import gradio as gr | |
import soundfile as sf | |
import tempfile | |
import shutil | |
import os | |
import librosa | |
import time | |
import numpy as np | |
import subprocess | |
from pywhispercpp.model import Model | |
# model = Model('base.en', n_threads=6,models_dir="./Models") # Only english | |
# model = Model('base', n_threads=6,models_dir="./Models",language="hindi",translate=False) # Multilingual | |
model = Model('medium-q5_0', n_threads=6,models_dir="./Models",language="hindi",translate=False) # Multilingual | |
def resample_to_16k(audio, orig_sr): | |
y_resampled = librosa.resample(y=audio, orig_sr=orig_sr, target_sr = 16000) | |
return y_resampled | |
def transcribe(audio): | |
print(type(audio)) | |
sr,y = audio | |
y = y.astype(np.float32) | |
y /= np.max(np.abs(y)) | |
y_resampled = resample_to_16k(y, sr) | |
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as temp_audio: | |
temp_audio_path = temp_audio.name | |
sf.write(temp_audio_path, y_resampled, 16000) | |
start_time_py = time.time() | |
py_result = model.transcribe(f'{temp_audio_path}', n_threads=6) | |
end_time_py = time.time() | |
print("Py_result : ",py_result) | |
print("--------------------------") | |
print(f"Execution time using py: {end_time_py - start_time_py} seconds") | |
output_text = "" | |
for segment in py_result: | |
output_text+=segment.text | |
return output_text, (end_time_py - start_time_py) | |
demo = gr.Interface( | |
transcribe, | |
inputs = "microphone", | |
# gr.Audio(sources=["microphone"]), | |
outputs=[gr.Textbox(label="Py_Transcription"),gr.Textbox(label="Time taken for Transcription")], | |
examples=["./Samples/Hindi_1.mp3","./Samples/Hindi_2.mp3","./Samples/Tamil_1.mp3","./Samples/Tamil_2.mp3","./Samples/Marathi_1.mp3","./Samples/Marathi_2.mp3","./Samples/Nepal_1.mp3","./Samples/Nepal_2.mp3","./Samples/Telugu_1.wav","./Samples/Telugu_2.wav","./Samples/Malayalam_1.wav","./Samples/Malayalam_2.wav","./Samples/Gujarati_1.wav","./Samples/Gujarati_2.wav","./Samples/Bengali_1.wav","./Samples/Bengali_2.wav"] | |
) | |
demo.launch() |