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from io import BytesIO
from typing import Tuple
import wave
import gradio as gr
import numpy as np
from pydub.audio_segment import AudioSegment
import requests
from os.path import exists
from stt import Model
# download model
storage_url = "https://coqui.gateway.scarf.sh/mixtec/jemeyer/v1.0.0"
model_name = "model.tflite"
model_link = f"{storage_url}/{model_name}"
def client(audio_data: np.array, sample_rate: int, use_scorer=False):
output_audio = _convert_audio(audio_data, sample_rate)
fin = wave.open(output_audio, 'rb')
audio = np.frombuffer(fin.readframes(fin.getnframes()), np.int16)
fin.close()
ds = Model(model_name)
if use_scorer:
ds.enableExternalScorer("kenlm.scorer")
result = ds.stt(audio)
return result
def download(url, file_name):
if not exists(file_name):
print(f"Downloading {file_name}")
r = requests.get(url, allow_redirects=True)
with open(file_name, 'wb') as file:
file.write(r.content)
else:
print(f"Found {file_name}. Skipping download...")
def stt(audio: Tuple[int, np.array]):
sample_rate, audio = audio
use_scorer = False
recognized_result = client(audio, sample_rate, use_scorer)
return recognized_result
def _convert_audio(audio_data: np.array, sample_rate: int):
source_audio = BytesIO()
source_audio.write(audio_data)
source_audio.seek(0)
output_audio = BytesIO()
wav_file = AudioSegment.from_raw(
source_audio,
channels=1,
sample_width=2,
frame_rate=sample_rate
)
wav_file.set_frame_rate(16000).set_channels(
1).export(output_audio, "wav", codec="pcm_s16le")
output_audio.seek(0)
return output_audio
iface = gr.Interface(
fn=stt,
inputs=[
gr.inputs.Audio(type="numpy",
label=None, optional=False),
],
outputs=gr.outputs.Textbox(label="Output"),
title="Coqui STT Yoloxochitl Mixtec",
theme="huggingface",
description="Prueba de dictado a texto para el mixteco de Yoloxochitl, usando [el modelo entrenado por Josh Meyer](https://coqui.ai/mixtec/jemeyer/v1.0.0/) con [los datos recopilados por Rey Castillo y sus colaboradoes](https://www.openslr.org/89). Esta prueba es basada en la de [Ukraniano](https://huggingface.co/spaces/robinhad/ukrainian-stt). \n\n"
"Speech-to-text demo for Yoloxochitl Mixtec, using [the model trained by Josh Meyer](https://coqui.ai/mixtec/jemeyer/v1.0.0/) on [the corpus compiled by Rey Castillo and collaborators](https://www.openslr.org/89). This demo is based on the [Ukrainian STT demo](https://huggingface.co/spaces/robinhad/ukrainian-stt).",
)
download(model_link, model_name)
iface.launch()
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