add basic HF space demo

NOTES.md

@@ -5,13 +5,13 @@
 ## Trained models
 
 ESPnet model for Yoloxochitl Mixtec 
- - Huggingface Hub page
+ - Huggingface Hub page https://huggingface.co/espnet/ftshijt_espnet2_asr_yolo_mixtec_transformer
  - Model source code https://github.com/espnet/espnet/tree/master/egs/yoloxochitl_mixtec/asr1
  - Colab notebook to setup and apply the model https://colab.research.google.com/drive/1ieoW2b3ERydjaaWuhVPBP_v2QqqWsC1Q?usp=sharing
  
 Coqui model for Yoloxochitl Mixtec
  - Huggingface Hub page
- - Coqui page
+ - Coqui page https://coqui.ai/mixtec/jemeyer/v1.0.0
  - Colab notebook to setup and apply the model https://colab.research.google.com/drive/1b1SujEGC_F3XhvUCuUyZK_tyUkEaFZ7D?usp=sharing#scrollTo=6IvRFke4Ckpz
 
 Spanish ASR models

app.py

@@ -0,0 +1,87 @@
+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], model_name: str):
+    sample_rate, audio = audio
+    use_scorer = False
+
+    if sample_rate != 16000:
+        raise ValueError("Incorrect sample rate.")
+
+    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="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).",
+)
+
+download(model_link, model_name)
+iface.launch()

packages.txt

@@ -0,0 +1 @@
+ffmpeg

requirements.txt

@@ -0,0 +1,3 @@
+gradio==2.4.5
+STT==1.0.0
+pydub==0.25.1