Hybrid context dependent CD-DNN-HMM keywords spotting on continuous speech

Abstract

In this paper we describe a systematic procedure to implement two-stage based keywords spotting system (KWS). In first stage, a phonetic decoding of continuous speech is obtained using a CD-DNN-HMM model built with the Kaldi toolkit. In second stage, these results of phonetic transcriptions will serve to construct a system to search the keywords embedded in continuous speech using the classification and regression tree (CART) implemented with the software MATLAB. The work will be done using the TIMIT data base.