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from io import BytesIO |
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from typing import Tuple |
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import wave |
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import gradio as gr |
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import numpy as np |
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from pydub.audio_segment import AudioSegment |
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import requests |
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from os.path import exists |
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from stt import Model |
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storage_url = "https://coqui.gateway.scarf.sh/mixtec/jemeyer/v1.0.0" |
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model_name = "model.tflite" |
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model_link = f"{storage_url}/{model_name}" |
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def client(audio_data: np.array, sample_rate: int, use_scorer=False): |
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output_audio = _convert_audio(audio_data, sample_rate) |
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fin = wave.open(output_audio, 'rb') |
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audio = np.frombuffer(fin.readframes(fin.getnframes()), np.int16) |
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fin.close() |
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ds = Model(model_name) |
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if use_scorer: |
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ds.enableExternalScorer("kenlm.scorer") |
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result = ds.stt(audio) |
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return result |
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def download(url, file_name): |
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if not exists(file_name): |
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print(f"Downloading {file_name}") |
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r = requests.get(url, allow_redirects=True) |
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with open(file_name, 'wb') as file: |
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file.write(r.content) |
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else: |
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print(f"Found {file_name}. Skipping download...") |
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def stt(audio: Tuple[int, np.array], model_name: str): |
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sample_rate, audio = audio |
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use_scorer = False |
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if sample_rate != 16000: |
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raise ValueError("Incorrect sample rate.") |
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recognized_result = client(audio, sample_rate, use_scorer) |
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return recognized_result |
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def _convert_audio(audio_data: np.array, sample_rate: int): |
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source_audio = BytesIO() |
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source_audio.write(audio_data) |
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source_audio.seek(0) |
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output_audio = BytesIO() |
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wav_file = AudioSegment.from_raw( |
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source_audio, |
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channels=1, |
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sample_width=2, |
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frame_rate=sample_rate |
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) |
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wav_file.set_frame_rate(16000).set_channels( |
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1).export(output_audio, "wav", codec="pcm_s16le") |
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output_audio.seek(0) |
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return output_audio |
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iface = gr.Interface( |
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fn=stt, |
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inputs=[ |
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gr.inputs.Audio(type="numpy", |
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label=None, optional=False), |
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], |
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outputs=gr.outputs.Textbox(label="Output"), |
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title="Coqui STT Yoloxochitl Mixtec", |
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theme="huggingface", |
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description="Speech-to-text demo for Yoloxochitl Mixtec, using the model trained by Josh Meyer on the corpus compiled by Rey Castillo and collaborators. This demo is based on the [Ukrainian STT demo](https://huggingface.co/spaces/robinhad/ukrainian-stt).", |
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) |
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download(model_link, model_name) |
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iface.launch() |
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