Upload app.py

app.py

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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()