Department of Computer Engineering2024-11-0920091558-791610.1109/TaSL.2009.20167332-s2.0-68549110984http://dx.doi.org/10.1109/TaSL.2009.2016733https://hdl.handle.net/20.500.14288/11379We present a new framework for joint analysis of throat and acoustic microphone (TaM) recordings to improve throat microphone only speech recognition. the proposed analysis framework aims to learn joint sub-phone patterns of throat and acoustic microphone recordings through a parallel branch HMM structure. the joint sub-phone patterns define temporally correlated neighborhoods, in which a linear prediction filter estimates a spectrally rich acoustic feature vector from throat feature vectors. Multimodal speech recognition with throat and throat-driven acoustic features significantly improves throat-only speech recognition performance. Experimental evaluations on a parallel TaM database yield benchmark phoneme recognition rates for throat-only and multimodal TaM speech recognition systems as 46.81% and 60.69%, respectively. the proposed throat-driven multimodal speech recognition system improves phoneme recognition rate to 52.58%, A significant relative improvement with respect to the throat-only speech recognition benchmark system.AcousticsElectrical electronics engineeringJournal Article1558-7924268172100006Q22879