A new combined model of statics-dynamics of speech

Linear prediction (LP) HMM does not make the independent and identical distribution (IID) assumption in traditional HMM; however it often produces unsatisfactory results. In this paper, a new combined model of statics-dynamics of speech is proposed, based on a new analysis of both HMM´s modeling strengths and weaknesses. The new model works with LPHMM as the dynamic part and traditional IID-based HMM as the static part; in addition, easy implementation and low cost are preserved. A new effective re-estimation solution is suggested for parameter tying to achieve better discrimination. Our experiments on speaker-independent continuous speech recognition demonstrated that the combined model achieved 7.5% error rate reduction from traditional HMM.