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Merge pull request #549 from snakers4/adamnsandle
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Adamnsandle
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adamnsandle authored Oct 9, 2024
2 parents 9c1eff9 + 001d57d commit 032ca21
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2 changes: 2 additions & 0 deletions examples/pyaudio-streaming/README.md
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Expand Up @@ -7,6 +7,8 @@ It has been designed as a low-level example for binary real-time streaming using
Currently, the notebook consits of two examples:
- One that records audio of a predefined length from the microphone, process it with Silero-VAD, and plots it afterwards.
- The other one plots the speech probabilities in real-time (using jupyterplot) and records the audio until you press enter.

This example does not work in google colab! For local usage only.

## Example Video for the Real-Time Visualization

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84 changes: 54 additions & 30 deletions examples/pyaudio-streaming/pyaudio-streaming-examples.ipynb
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"cells": [
{
"cell_type": "markdown",
"id": "62a0cccb",
"id": "76aa55ba",
"metadata": {},
"source": [
"# Pyaudio Microphone Streaming Examples\n",
Expand All @@ -12,12 +12,14 @@
"I created it as an example on how binary data from a stream could be feed into Silero VAD.\n",
"\n",
"\n",
"Has been tested on Ubuntu 21.04 (x86). After you installed the dependencies below, no additional setup is required."
"Has been tested on Ubuntu 21.04 (x86). After you installed the dependencies below, no additional setup is required.\n",
"\n",
"This notebook does not work in google colab! For local usage only."
]
},
{
"cell_type": "markdown",
"id": "64cbe1eb",
"id": "4a4e15c2",
"metadata": {},
"source": [
"## Dependencies\n",
Expand All @@ -26,33 +28,55 @@
},
{
"cell_type": "code",
"execution_count": null,
"id": "57bc2aac",
"metadata": {},
"execution_count": 1,
"id": "24205cce",
"metadata": {
"ExecuteTime": {
"end_time": "2024-10-09T08:47:34.056898Z",
"start_time": "2024-10-09T08:47:34.053418Z"
}
},
"outputs": [],
"source": [
"#!pip install numpy==2.0.2\n",
"#!pip install torch==2.4.1\n",
"#!pip install matplotlib==3.9.2\n",
"#!pip install torchaudio==2.4.1\n",
"#!pip install numpy>=1.24.0\n",
"#!pip install torch>=1.12.0\n",
"#!pip install matplotlib>=3.6.0\n",
"#!pip install torchaudio>=0.12.0\n",
"#!pip install soundfile==0.12.1\n",
"#!pip install pyaudio==0.2.11"
"#!apt install python3-pyaudio (linux) or pip install pyaudio (windows)"
]
},
{
"cell_type": "markdown",
"id": "110de761",
"id": "cd22818f",
"metadata": {},
"source": [
"## Imports"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5a647d8d",
"metadata": {},
"outputs": [],
"execution_count": 2,
"id": "994d7f3a",
"metadata": {
"ExecuteTime": {
"end_time": "2024-10-09T08:47:39.005032Z",
"start_time": "2024-10-09T08:47:36.489952Z"
}
},
"outputs": [
{
"ename": "ModuleNotFoundError",
"evalue": "No module named 'pyaudio'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[2], line 8\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mmatplotlib\u001b[39;00m\n\u001b[1;32m 7\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mmatplotlib\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpylab\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mplt\u001b[39;00m\n\u001b[0;32m----> 8\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpyaudio\u001b[39;00m\n",
"\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'pyaudio'"
]
}
],
"source": [
"import io\n",
"import numpy as np\n",
Expand All @@ -67,7 +91,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "725d7066",
"id": "ac5c52f7",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -79,7 +103,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "1c0b2ea7",
"id": "ad5919dc",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -92,7 +116,7 @@
},
{
"cell_type": "markdown",
"id": "f9112603",
"id": "784d1ab6",
"metadata": {},
"source": [
"### Helper Methods"
Expand All @@ -101,7 +125,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "5abc6330",
"id": "af4bca64",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -124,7 +148,7 @@
},
{
"cell_type": "markdown",
"id": "5124095e",
"id": "ca13e514",
"metadata": {},
"source": [
"## Pyaudio Set-up"
Expand All @@ -133,7 +157,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "a845356e",
"id": "75f99022",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -147,7 +171,7 @@
},
{
"cell_type": "markdown",
"id": "0b910c99",
"id": "4da7d2ef",
"metadata": {},
"source": [
"## Simple Example\n",
Expand All @@ -157,7 +181,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "9d3d2c10",
"id": "6fe77661",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -167,7 +191,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "3cb44a4a",
"id": "23f4da3e",
"metadata": {},
"outputs": [],
"source": [
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},
{
"cell_type": "markdown",
"id": "a3dda982",
"id": "fd243e8f",
"metadata": {},
"source": [
"## Real Time Visualization\n",
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{
"cell_type": "code",
"execution_count": null,
"id": "05ef4100",
"id": "d36980c2",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -230,7 +254,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "d1d4cdd6",
"id": "5607b616",
"metadata": {},
"outputs": [],
"source": [
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{
"cell_type": "code",
"execution_count": null,
"id": "1e398009",
"id": "dc4f0108",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -311,7 +335,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.10"
"version": "3.10.14"
},
"toc": {
"base_numbering": 1,
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