Vocal Tract Resonances Tracking by Auziliary Particle Filters
This paper presents an auxiliary particle filtering method for vocal tract resonances (VTRs) tracking. The proposed method is based on a version of the structured speech model, with a state-space formulation consisting of target-guided dynamics and a non-linear prediction mapping from resonance frequencies and bandwidths to Linear Prediction Coding Cepstra (LPCC). In conventional particle filter, the particles are generated from the transition prior can easily land on low-likelihood areas thus wasted. To overcome this difficulty, we explore a novel algorithm to generate sophisticated proposal distribution that integrates the phoneme information by introducing an auxiliary vector. Experimental results show that due to the improvement of proposal distribution, the proposed method is able to track the VTRs efficiently using a small number of particles both in the vocalic regions and the consonantal regions of the speech utterance.
Yebin Wang Heming Zhao
School of Electronics and Information Engineering Soochow University, Suzhou, Jiangsu, China
国际会议
2008 International Conference on Audio，Language and Image Processing(2008国际声音、语言、图像过程大会)
镇江
英文
1131-1134
2008-07-07（万方平台首次上网日期，不代表论文的发表时间）