mirror of
https://github.com/snakers4/silero-vad.git
synced 2026-02-05 18:09:22 +08:00
add adaptive examples
This commit is contained in:
adamnsandle
260
silero-vad.ipynb
260
silero-vad.ipynb
@@ -3,6 +3,7 @@
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{
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"cell_type": "markdown",
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"metadata": {
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"heading_collapsed": true,
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"id": "sVNOuHQQjsrp"
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},
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"source": [
|
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@@ -12,7 +13,8 @@
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{
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"cell_type": "markdown",
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"metadata": {
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"heading_collapsed": true
|
||||
"heading_collapsed": true,
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"hidden": true
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},
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"source": [
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"## VAD"
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@@ -57,6 +59,7 @@
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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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" get_speech_ts_adaptive,\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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@@ -77,6 +80,15 @@
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"### Full Audio"
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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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"hidden": true
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||||
},
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"source": [
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"**Classic way of getting speech chunks, you may need to select the tresholds yourself**"
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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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@@ -116,6 +128,43 @@
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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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"hidden": true
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||||
},
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"source": [
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"**Experimental Adaptive method, algorythm selects tresholds itself (see readme for more information)**"
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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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"hidden": true
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},
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"outputs": [],
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"source": [
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"wav = read_audio(f'{files_dir}/en.wav')\n",
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"# get speech timestamps from full audio file\n",
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"speech_timestamps = get_speech_ts_adaptive(wav, model, step=500, num_samples_per_window=4000)\n",
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"pprint(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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"hidden": true
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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_chunks(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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@@ -127,6 +176,19 @@
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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": "markdown",
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"metadata": {
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"ExecuteTime": {
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||||
"end_time": "2021-04-15T13:29:04.224833Z",
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"start_time": "2021-04-15T13:29:04.220588Z"
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},
|
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"hidden": true
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},
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"source": [
|
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"**Classic way of getting speech chunks, you may need to select the tresholds yourself**"
|
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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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@@ -147,6 +209,30 @@
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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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"hidden": true
|
||||
},
|
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"source": [
|
||||
"**Experimental Adaptive method, algorythm selects tresholds itself (see readme for more information)**"
|
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]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
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||||
"execution_count": null,
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"metadata": {
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"hidden": true
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},
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"outputs": [],
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"source": [
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"wav = f'{files_dir}/en.wav'\n",
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"\n",
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"for batch in single_audio_stream(model, wav, iterator_type='adaptive'):\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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@@ -196,7 +282,8 @@
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{
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"cell_type": "markdown",
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"metadata": {
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"heading_collapsed": true
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"heading_collapsed": true,
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"hidden": true
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},
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"source": [
|
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"## Number detector"
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@@ -315,7 +402,8 @@
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{
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"cell_type": "markdown",
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"metadata": {
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"heading_collapsed": true
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"heading_collapsed": true,
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"hidden": true
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},
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"source": [
|
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"## Language detector"
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@@ -387,6 +475,7 @@
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{
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"cell_type": "markdown",
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"metadata": {
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"heading_collapsed": true,
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"id": "57avIBd6jsrz"
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},
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"source": [
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@@ -396,7 +485,8 @@
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{
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"cell_type": "markdown",
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"metadata": {
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"heading_collapsed": true
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"heading_collapsed": true,
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"hidden": true
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},
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"source": [
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"## VAD"
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@@ -415,13 +505,29 @@
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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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"execution_count": 3,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2021-04-15T13:30:22.938755Z",
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"start_time": "2021-04-15T13:30:20.970574Z"
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},
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"cellView": "form",
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"hidden": true,
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"id": "Q4QIfSpprnkI"
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},
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"outputs": [],
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"outputs": [
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{
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"ename": "NameError",
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"evalue": "name 'torch' is not defined",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m\u001b[0m",
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"\u001b[0;31mNameError\u001b[0mTraceback (most recent call last)",
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"\u001b[0;32m<ipython-input-3-ca9e92528117>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mIPython\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdisplay\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mAudio\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m _, utils = torch.hub.load(repo_or_dir='snakers4/silero-vad',\n\u001b[0m\u001b[1;32m 13\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'silero_vad'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 14\u001b[0m force_reload=True)\n",
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"\u001b[0;31mNameError\u001b[0m: name 'torch' is not defined"
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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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@@ -439,6 +545,7 @@
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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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" get_speech_ts_adaptive,\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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@@ -470,17 +577,42 @@
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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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"cell_type": "markdown",
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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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||||
"end_time": "2021-04-15T13:34:22.554010Z",
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||||
"start_time": "2021-04-15T13:34:22.550308Z"
|
||||
},
|
||||
"hidden": true
|
||||
},
|
||||
"source": [
|
||||
"**Classic way of getting speech chunks, you may need to select the tresholds yourself**"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
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||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2021-04-15T13:30:14.475412Z",
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||||
"start_time": "2021-04-15T13:30:14.427933Z"
|
||||
},
|
||||
"hidden": true,
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||||
"id": "krnGoA6Kjsr0"
|
||||
},
|
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"outputs": [],
|
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"outputs": [
|
||||
{
|
||||
"ename": "NameError",
|
||||
"evalue": "name 'init_onnx_model' is not defined",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
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"\u001b[0;31m\u001b[0m",
|
||||
"\u001b[0;31mNameError\u001b[0mTraceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-2-65cde4c4cba8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmodel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0minit_onnx_model\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf'{files_dir}/model.onnx'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mwav\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mread_audio\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf'{files_dir}/en.wav'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;31m# get speech timestamps from full audio file\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mspeech_timestamps\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_speech_ts\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwav\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnum_steps\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m4\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrun_function\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvalidate_onnx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;31mNameError\u001b[0m: name 'init_onnx_model' is not defined"
|
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]
|
||||
}
|
||||
],
|
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"source": [
|
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"model = init_onnx_model(f'{files_dir}/model.onnx')\n",
|
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"wav = read_audio(f'{files_dir}/en.wav')\n",
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@@ -508,6 +640,60 @@
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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",
|
||||
"metadata": {
|
||||
"hidden": true
|
||||
},
|
||||
"source": [
|
||||
"**Experimental Adaptive method, algorythm selects tresholds itself (see readme for more information)**"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"hidden": true
|
||||
},
|
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"outputs": [],
|
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"source": [
|
||||
"model = init_onnx_model(f'{files_dir}/model.onnx')\n",
|
||||
"wav = read_audio(f'{files_dir}/en.wav')\n",
|
||||
"\n",
|
||||
"# get speech timestamps from full audio file\n",
|
||||
"speech_timestamps = get_speech_ts_adaptive(wav, model, run_function=validate_onnx) \n",
|
||||
"pprint(speech_timestamps)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2021-04-15T13:34:41.375446Z",
|
||||
"start_time": "2021-04-15T13:34:41.368055Z"
|
||||
},
|
||||
"hidden": true
|
||||
},
|
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"outputs": [
|
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{
|
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"ename": "NameError",
|
||||
"evalue": "name 'save_audio' is not defined",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;31m\u001b[0m",
|
||||
"\u001b[0;31mNameError\u001b[0mTraceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-5-713048adde74>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# merge all speech chunks to one audio\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0msave_audio\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'only_speech.wav'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcollect_chunks\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mspeech_timestamps\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwav\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m16000\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0mAudio\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'only_speech.wav'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;31mNameError\u001b[0m: name 'save_audio' is not defined"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# merge all speech chunks to one audio\n",
|
||||
"save_audio('only_speech.wav', collect_chunks(speech_timestamps, wav), 16000)\n",
|
||||
"Audio('only_speech.wav')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
@@ -519,6 +705,15 @@
|
||||
"### Single Audio Stream"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"hidden": true
|
||||
},
|
||||
"source": [
|
||||
"**Classic way of getting speech chunks, you may need to select the tresholds yourself**"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
@@ -554,6 +749,40 @@
|
||||
" pprint(batch)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"hidden": true
|
||||
},
|
||||
"source": [
|
||||
"**Experimental Adaptive method, algorythm selects tresholds itself (see readme for more information)**"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"hidden": true
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"model = init_onnx_model(f'{files_dir}/model.onnx')\n",
|
||||
"wav = f'{files_dir}/en.wav'"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"hidden": true
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"for batch in single_audio_stream(model, wav, iterator_type='adaptive', run_function=validate_onnx):\n",
|
||||
" if batch:\n",
|
||||
" pprint(batch)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
@@ -604,7 +833,8 @@
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"heading_collapsed": true
|
||||
"heading_collapsed": true,
|
||||
"hidden": true
|
||||
},
|
||||
"source": [
|
||||
"## Number detector"
|
||||
@@ -753,7 +983,8 @@
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"heading_collapsed": true
|
||||
"heading_collapsed": true,
|
||||
"hidden": true
|
||||
},
|
||||
"source": [
|
||||
"## Language detector"
|
||||
@@ -819,7 +1050,6 @@
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"heading_collapsed": true,
|
||||
"hidden": true,
|
||||
"id": "5JHErdB7jsr0"
|
||||
},
|
||||
@@ -863,7 +1093,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.3"
|
||||
"version": "3.8.8"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
||||
Reference in New Issue
Block a user