mirror of
https://github.com/snakers4/silero-vad.git
synced 2026-02-04 17:39:22 +08:00
440 lines
10 KiB
Plaintext
440 lines
10 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "sVNOuHQQjsrp"
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},
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"source": [
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"# PyTorch Example"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "9ZTzCtc5kYVg"
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},
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"source": [
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"## Install Dependencies"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2020-12-15T14:00:15.701867Z",
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"start_time": "2020-12-15T14:00:09.512876Z"
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},
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"cellView": "form",
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"id": "rllMjjsekbjt"
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},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Downloading: \"https://github.com/snakers4/silero-vad/archive/master.zip\" to /home/keras/.cache/torch/hub/master.zip\n",
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"/opt/conda/lib/python3.8/site-packages/torchaudio/backend/utils.py:53: UserWarning: \"sox\" backend is being deprecated. The default backend will be changed to \"sox_io\" backend in 0.8.0 and \"sox\" backend will be removed in 0.9.0. Please migrate to \"sox_io\" backend. Please refer to https://github.com/pytorch/audio/issues/903 for the detail.\n",
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" warnings.warn(\n",
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"/opt/conda/lib/python3.8/site-packages/torchaudio/backend/utils.py:63: UserWarning: The interface of \"soundfile\" backend is planned to change in 0.8.0 to match that of \"sox_io\" backend and the current interface will be removed in 0.9.0. To use the new interface, do `torchaudio.USE_SOUNDFILE_LEGACY_INTERFACE = False` before setting the backend to \"soundfile\". Please refer to https://github.com/pytorch/audio/issues/903 for the detail.\n",
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" warnings.warn(\n"
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]
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}
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],
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"source": [
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"#@title Install and Import Dependencies\n",
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"\n",
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"# this assumes that you have a relevant version of PyTorch installed\n",
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"#!pip install -q torchaudio soundfile\n",
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"\n",
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"import glob\n",
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"import torch\n",
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"torch.set_num_threads(1)\n",
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"\n",
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"from IPython.display import Audio\n",
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"\n",
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"\n",
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"model, utils = torch.hub.load(repo_or_dir='snakers4/silero-vad',\n",
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" model='silero_vad',\n",
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" force_reload=True)\n",
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"\n",
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"(get_speech_ts,\n",
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" save_audio,\n",
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" read_audio,\n",
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" state_generator,\n",
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" single_audio_stream,\n",
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" collect_speeches) = utils"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2020-12-15T14:03:38.006309Z",
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"start_time": "2020-12-15T14:03:38.002613Z"
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}
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'/home/keras/.cache/torch/hub'"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"torch.hub.get_dir()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "fXbbaUO3jsrw"
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},
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"source": [
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"## Full audio"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2020-12-15T13:09:56.879818Z",
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"start_time": "2020-12-15T13:09:56.864765Z"
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},
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"id": "aI_eydBPjsrx"
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},
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"outputs": [],
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"source": [
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"wav = read_audio('files/en.wav')\n",
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"# get speech timestamps from full audio file\n",
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"speech_timestamps = get_speech_ts(wav, model,\n",
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" num_steps=4)\n",
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"print(speech_timestamps)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2020-12-15T13:09:58.941063Z",
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"start_time": "2020-12-15T13:09:58.887006Z"
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},
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"id": "OuEobLchjsry"
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},
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"outputs": [],
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"source": [
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"# merge all speech chunks to one audio\n",
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"save_audio('only_speech.wav',\n",
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" collect_speeches(speech_timestamps, wav), 16000) \n",
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"Audio('only_speech.wav')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "iDKQbVr8jsry"
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},
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"source": [
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"## Single Audio Stream"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2020-12-15T13:09:59.199321Z",
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"start_time": "2020-12-15T13:09:59.196823Z"
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},
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"id": "q-lql_2Wjsry"
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},
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"outputs": [],
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"source": [
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"wav = 'files/en.wav'\n",
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"\n",
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"for batch in single_audio_stream(model, wav):\n",
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" if batch:\n",
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" print(batch)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "KBDVybJCjsrz"
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},
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"source": [
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"## Multiple Audio Streams"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2020-12-15T13:10:03.590358Z",
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"start_time": "2020-12-15T13:10:03.587071Z"
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},
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"id": "BK4tGfWgjsrz"
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},
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"outputs": [],
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"source": [
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"audios_for_stream = glob.glob('files/*.wav')\n",
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"len(audios_for_stream) # total 4 audios"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2020-12-15T13:10:15.762491Z",
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"start_time": "2020-12-15T13:10:03.591388Z"
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},
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"id": "v1l8sam1jsrz"
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},
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"outputs": [],
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"source": [
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"for batch in state_generator(model, audios_for_stream, audios_in_stream=2): # 2 audio stream\n",
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" if batch:\n",
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" print(batch)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "57avIBd6jsrz"
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},
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"source": [
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"# ONNX Example"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "bL4kn4KJrlyL"
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},
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"source": [
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"## Install Dependencies"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "Q4QIfSpprnkI"
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},
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"outputs": [],
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"source": [
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"#@title Install and Import Dependencies\n",
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"\n",
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"# this assumes that you have a relevant version of PyTorch installed\n",
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"!pip install -q torchaudio soundfile onnxruntime\n",
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"\n",
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"import glob\n",
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"import onnxruntime\n",
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"\n",
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"from IPython.display import Audio\n",
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"\n",
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"_, utils = torch.hub.load(repo_or_dir='snakers4/silero-vad',\n",
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" model='silero_vad',\n",
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" force_reload=True)\n",
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"\n",
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"(get_speech_ts,\n",
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" save_audio,\n",
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" read_audio,\n",
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" state_generator,\n",
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" single_audio_stream,\n",
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" collect_speeches) = utils\n",
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"\n",
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" def init_onnx_model(model_path: str):\n",
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" return onnxruntime.InferenceSession(model_path)\n",
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"\n",
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"def validate_onnx(model, inputs):\n",
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" with torch.no_grad():\n",
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" ort_inputs = {'input': inputs.cpu().numpy()}\n",
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" outs = model.run(None, ort_inputs)\n",
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" outs = [torch.Tensor(x) for x in outs]\n",
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" return outs"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "5JHErdB7jsr0"
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},
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"source": [
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"## Full audio"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2020-12-15T13:09:06.643812Z",
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"start_time": "2020-12-15T13:09:06.473386Z"
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},
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"id": "krnGoA6Kjsr0"
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},
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"outputs": [],
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"source": [
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"model = init_onnx_model('files/model.onnx')\n",
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"wav = read_audio('files/en.wav')\n",
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"\n",
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"# get speech timestamps from full audio file\n",
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"speech_timestamps = get_speech_ts(wav, model, num_steps=4, run_function=validate_onnx) \n",
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"print(speech_timestamps)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2020-12-15T13:09:08.862421Z",
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"start_time": "2020-12-15T13:09:08.820014Z"
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},
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"id": "B176Lzfnjsr1"
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},
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"outputs": [],
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"source": [
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"# merge all speech chunks to one audio\n",
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"save_audio('only_speech.wav', collect_speeches(speech_timestamps, wav), 16000)\n",
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"Audio('only_speech.wav')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "Rio9W50gjsr1"
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},
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"source": [
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"## Single audio stream"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2020-12-15T13:09:09.606031Z",
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"start_time": "2020-12-15T13:09:09.504239Z"
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},
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"id": "IPkl8Yy1jsr1"
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},
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"outputs": [],
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"source": [
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"model = init_onnx_model('files/model.onnx')\n",
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"wav = 'files/en.wav'"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2020-12-15T13:09:11.453171Z",
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"start_time": "2020-12-15T13:09:09.633435Z"
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},
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"id": "NC6Jim0hjsr1"
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},
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"outputs": [],
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"source": [
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"for batch in single_audio_stream(model, wav, run_function=validate_onnx):\n",
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" if batch:\n",
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" print(batch)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "WNZ42u0ajsr1"
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},
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"source": [
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"## Multiple audio stream"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2020-12-15T13:09:11.540423Z",
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"start_time": "2020-12-15T13:09:11.455706Z"
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},
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"id": "XjhGQGppjsr1"
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},
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"outputs": [],
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"source": [
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"model = init_onnx_model('files/model.onnx')\n",
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"audios_for_stream = glob.glob('files/*.wav')\n",
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"print(len(audios_for_stream)) # total 4 audios"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2020-12-15T13:09:19.565434Z",
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"start_time": "2020-12-15T13:09:11.552097Z"
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},
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"id": "QI7-arlqjsr2"
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},
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"outputs": [],
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"source": [
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"for batch in state_generator(model, audios_for_stream, audios_in_stream=2, run_function=validate_onnx): # 2 audio stream\n",
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" if batch:\n",
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" print(batch)"
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]
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}
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],
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"metadata": {
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"colab": {
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"name": "silero-vad.ipynb",
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"provenance": []
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},
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.3"
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},
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"toc": {
|
|
"base_numbering": 1,
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|
"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
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}
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|
},
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|
"nbformat": 4,
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|
"nbformat_minor": 1
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}
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