A new speech recognition method is proposed, that integrates a VQ distortion measure and a discrete HMM. This VQ distortion based HMM uses a VQ distortion measure at each state instead of a discrete probability out...A new speech recognition method is proposed, that integrates a VQ distortion measure and a discrete HMM. This VQ distortion based HMM uses a VQ distortion measure at each state instead of a discrete probability output used by a discrete HMM. Although this method is regarded as a refined version of the VQ distortion based recognition method proposed by Burton et al, it is also considered as a special case of a mixed distribution density HMM. In this paper, the VQ distortion based HMM is described, and it is compared with the conventional HMMs and their speech recognition performance through the experiments on speaker independent spoken digit recognition. From these comparisons, we confirm that the new method is better than the traditional HMMs.展开更多
Two discriminative methods for solving tone problems in Mandarin speech recognition are presented. First, discriminative training on the HMM （hidden Markov model） based tone models is proposed. Then an integration t...Two discriminative methods for solving tone problems in Mandarin speech recognition are presented. First, discriminative training on the HMM （hidden Markov model） based tone models is proposed. Then an integration technique of tone models into a large vocabulary continuous speech recognition system is presented. Discriminative model weight training based on minimum phone error criteria is adopted aiming at optimal integration of the tone models. The extended Baum Welch algorithm is applied to find the model-dependent weights to scale the acoustic scores and tone scores. Experimental results show that tone recognition rates and continuous speech recognition accuracy can be improved by the discriminatively trained tone model. Performance of a large vocabulary continuous Mandarin speech recognition system can be further enhanced by the discriminatively trained weight combinations due to a better interpolation of the given models.展开更多
This work is concerned with identification of systems that are subject to not only measurement noises, but also structural uncertainties such as unmodeled dynamics, sensor nonlinear mismatch, and observation bins. Ide...This work is concerned with identification of systems that are subject to not only measurement noises, but also structural uncertainties such as unmodeled dynamics, sensor nonlinear mismatch, and observation bins. Identification errors are analyzed for their dependence on these structural uncertainties. Asymptotic distributions of scaled sequences of estimation errors are derived.展开更多
文摘A new speech recognition method is proposed, that integrates a VQ distortion measure and a discrete HMM. This VQ distortion based HMM uses a VQ distortion measure at each state instead of a discrete probability output used by a discrete HMM. Although this method is regarded as a refined version of the VQ distortion based recognition method proposed by Burton et al, it is also considered as a special case of a mixed distribution density HMM. In this paper, the VQ distortion based HMM is described, and it is compared with the conventional HMMs and their speech recognition performance through the experiments on speaker independent spoken digit recognition. From these comparisons, we confirm that the new method is better than the traditional HMMs.
文摘Two discriminative methods for solving tone problems in Mandarin speech recognition are presented. First, discriminative training on the HMM （hidden Markov model） based tone models is proposed. Then an integration technique of tone models into a large vocabulary continuous speech recognition system is presented. Discriminative model weight training based on minimum phone error criteria is adopted aiming at optimal integration of the tone models. The extended Baum Welch algorithm is applied to find the model-dependent weights to scale the acoustic scores and tone scores. Experimental results show that tone recognition rates and continuous speech recognition accuracy can be improved by the discriminatively trained tone model. Performance of a large vocabulary continuous Mandarin speech recognition system can be further enhanced by the discriminatively trained weight combinations due to a better interpolation of the given models.
文摘This work is concerned with identification of systems that are subject to not only measurement noises, but also structural uncertainties such as unmodeled dynamics, sensor nonlinear mismatch, and observation bins. Identification errors are analyzed for their dependence on these structural uncertainties. Asymptotic distributions of scaled sequences of estimation errors are derived.
