mirror of
https://github.com/snakers4/silero-vad.git
synced 2026-02-05 01:49:22 +08:00
162 lines
4.2 KiB
Plaintext
162 lines
4.2 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Install Dependencies"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# !pip install -q torchaudio\n",
|
|
"SAMPLING_RATE = 16000\n",
|
|
"import torch\n",
|
|
"from pprint import pprint\n",
|
|
"import time\n",
|
|
"import shutil\n",
|
|
"\n",
|
|
"torch.set_num_threads(1)\n",
|
|
"NUM_PROCESS=4 # set to the number of CPU cores in the machine\n",
|
|
"NUM_COPIES=8\n",
|
|
"# download wav files, make multiple copies\n",
|
|
"torch.hub.download_url_to_file('https://models.silero.ai/vad_models/en.wav', f\"en_example0.wav\")\n",
|
|
"for idx in range(NUM_COPIES-1):\n",
|
|
" shutil.copy(f\"en_example0.wav\", f\"en_example{idx+1}.wav\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Load VAD model from torch hub"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"model, utils = torch.hub.load(repo_or_dir='snakers4/silero-vad',\n",
|
|
" model='silero_vad',\n",
|
|
" force_reload=True,\n",
|
|
" onnx=False)\n",
|
|
"\n",
|
|
"(get_speech_timestamps,\n",
|
|
"save_audio,\n",
|
|
"read_audio,\n",
|
|
"VADIterator,\n",
|
|
"collect_chunks) = utils"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Define a vad process function"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import multiprocessing\n",
|
|
"\n",
|
|
"vad_models = dict()\n",
|
|
"\n",
|
|
"def init_model(model):\n",
|
|
" pid = multiprocessing.current_process().pid\n",
|
|
" model, _ = torch.hub.load(repo_or_dir='snakers4/silero-vad',\n",
|
|
" model='silero_vad',\n",
|
|
" force_reload=False,\n",
|
|
" onnx=False)\n",
|
|
" vad_models[pid] = model\n",
|
|
"\n",
|
|
"def vad_process(audio_file: str):\n",
|
|
" \n",
|
|
" pid = multiprocessing.current_process().pid\n",
|
|
" \n",
|
|
" with torch.no_grad():\n",
|
|
" wav = read_audio(audio_file, sampling_rate=SAMPLING_RATE)\n",
|
|
" return get_speech_timestamps(\n",
|
|
" wav,\n",
|
|
" vad_models[pid],\n",
|
|
" 0.46, # speech prob threshold\n",
|
|
" 16000, # sample rate\n",
|
|
" 300, # min speech duration in ms\n",
|
|
" 20, # max speech duration in seconds\n",
|
|
" 600, # min silence duration\n",
|
|
" 512, # window size\n",
|
|
" 200, # spech pad ms\n",
|
|
" )"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Parallelization"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"from concurrent.futures import ProcessPoolExecutor, as_completed\n",
|
|
"\n",
|
|
"futures = []\n",
|
|
"\n",
|
|
"with ProcessPoolExecutor(max_workers=NUM_PROCESS, initializer=init_model, initargs=(model,)) as ex:\n",
|
|
" for i in range(NUM_COPIES):\n",
|
|
" futures.append(ex.submit(vad_process, f\"en_example{idx}.wav\"))\n",
|
|
"\n",
|
|
"for finished in as_completed(futures):\n",
|
|
" pprint(finished.result())"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.10.14"
|
|
},
|
|
"toc": {
|
|
"base_numbering": 1,
|
|
"nav_menu": {},
|
|
"number_sections": true,
|
|
"sideBar": true,
|
|
"skip_h1_title": false,
|
|
"title_cell": "Table of Contents",
|
|
"title_sidebar": "Contents",
|
|
"toc_cell": false,
|
|
"toc_position": {},
|
|
"toc_section_display": true,
|
|
"toc_window_display": false
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|