Python Hotword Detection
This library provides functionality for detecting a hotword in given audio file using MFCC features and Dynamic Time Warping (DTW) pattern matching algorithm.
This project is on pypi
To install from pypi:
pip install hotword_detection
From this repository:
git clone https://github.com/sakethgsharma/HotWordDetection.git python setup.py install
For training a hotword, run:
For testing, run:
- Mel Frequency Cepstral Coefficients
- Choice of selecting any suitable hot word through appropriate training paradigm
- Supports variable sampling frequencies
- Amplitude based Voice Activity Detector(VAD) used during recordings to remove extraneous noise
- Personalization using automatic DTW thresholding
MFCC vectors are used in this module since they are the most commonly extracted features used for speech recognition systems.
|alpha||Parameter used in pre-emphasis filtering. Should be any value between 0 and 1.|
|N||Number of FFT points.|
|fs||Sampling frequency of stored audio file.|
|frame_dur||Duration of 1 speech frame.|
|num_filters||Number of filters used in the Mel filterbank.|
|lower_freq||Lower frequency bound used for constructing filterbank.|
|upper_freq||Upper frequency bound used for constructing filterbank. Should be less than fs/2.|
Dynamic Time Warping
Dynamic time warping (DTW) is an algorithm for measuring similarity between two temporal sequences which may vary in speed.
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