pyrtstools 0.2.6

Tools for real time speech processing, keyword spotting (compatibility for python 3.5 and earlier)

PyRTSTools

Introduction

Python Real Time Speech Tools is a collection of classes designed to develop a real-time speech processing pipeline for voice user interface.

Disclaimer: This is an early version designed to provide a voice command detection pipeline for LinTO. However the elements are designed to be generic and can be used for other purposes.

Features

pyrtstools features different blocks:

• Audio acquisition
• Voice activity detection
• Feature extraction
• Keyword spotting

All the element are designed to be easy to use and easy to interconnect.

Installation

In order to install the package you need python3 and pip/setuptools installed.

Recquired libraries are:

• portaudio19-dev (For pyaudio microphone input)

The python dependecies are automaticly installed. (Note that it may takes some time as some of them -numpy, tensorflow- are faily large)

pypi

sudo pip3 install pyrtstools

From source

git clone https://github.com/linto-ai/pyrtstools.git
cd pyrtstools
sudo ./setup.py install

Usage

Here are a simple pipeline designed to detect hotword from microphone

import pyrtstools as rts

audioParam = rts.listenner.AudioParams() # Hold signal parameters
listenner = rts.listenner.Listenner(audioParam) # Microphone input
vad = rts.vad.VADer() # Voice activity detection
btn = rts.transform.ByteToNum(normalize=True) #Convert raw signal to numerical
featParams = rts.features.MFCCParams() # Hold MFCC features parameters
mfcc = rts.features.SonopyMFCC(featParams) # Extract MFCC
kws = rts.kws.KWS("/path/to/your-model.pb", (30,13)) # Hotword spotting 
pipeline = rts.Pipeline([listenner, vad, btn, mfcc, kws]) # Holds elements and links them
pipeline.start() # Start all the elements
try:
    listenner.join() # Wait for the microphone to finish (To block the execution)
except KeyboardInterrupt:
    pipeline.close()

Every block is located in a subpackage:

• Audio acquisition: pyrtstools.listenner
• Voice activity detection: pyrtstools.vad
• Features extraction: pyrtstools.features
• Keyword spotting: pyrtstools.kws
• Signal transformation: pyrtstools.transform

Every element and class is documented.

Licence

This project is under aGPLv3 licence, feel free to use and modify the code under those terms. See LICENCE

Used libraries

• Numpy
• Tensorflow / keras
• Sonopy
• pyaudio
• py-webrtcvad