Keyword spotting -- Detecting commands in speech using deep learning
Sumedha Rai Tong Li Bella Lyu
Speech recognition has become an important task in the development of machine
learning and artificial intelligence. In this study, we explore the important
task of keyword spotting using speech recognition machine learning and deep
learning techniques. We implement feature engineering by converting raw
waveforms to Mel Frequency Cepstral Coefficients (MFCCs), which we use as
inputs to our models. We experiment with several different algorithms such as
Hidden Markov Model with Gaussian Mixture, Convolutional Neural Networks and
variants of Recurrent Neural Networks including Long Short-Term Memory and the
Attention mechanism. In our experiments, RNN with BiLSTM and Attention achieves
the best performance with an accuracy of 93.9 %