论文信息 - Statistical approach to vocal tract transfer function estimation based on factor analyzed trajectory HMM

Statistical approach to vocal tract transfer function estimation based on factor analyzed trajectory HMM

In this paper, we describe a novel statistical approach to the vocal tract transfer function (VTTF) estimation of a speech signal based on a factor analyzed trajectory hidden Markov model (HMM). Because speech is a quasi-periodic signal, there are many missing frequency components between adjacent Fo harmonics. The proposed method determines a time-varying VTTF sequence based on the maximum a posteriori (MAP) estimation considering not only harmonic components observed at each analyzed frame but also those at other frames for stochastically interpolating the missing frequency parts.

Keiichi Tokuda | Tomoki Toda | K. Tokuda | T. Toda

[1] Keiichi Tokuda,et al. Mel-generalized cepstral analysis - a unified approach to speech spectral estimation , 1994, ICSLP.

[2] Koichi Shinoda,et al. MDL-based context-dependent subword modeling for speech recognition , 2000 .

[3] F. Itakura,et al. A statistical method for estimation of speech spectral density and formant frequencies , 1970 .

[4] Takehiko Kagoshima,et al. Analytic generation of synthesis units by closed loop training for totally speaker driven text to speech system (TOS drive TTS) , 1998, ICSLP.

[5] Heiga Zen,et al. Reformulating the HMM as a trajectory model by imposing explicit relationships between static and dynamic feature vector sequences , 2007, Comput. Speech Lang..

[6] Dong Yu,et al. Structured speech modeling , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[7] Simon King,et al. Estimating the spectral envelope of voiced speech using multi-frame analysis , 2003, INTERSPEECH.

[8] Hideki Kawahara,et al. Restructuring speech representations using a pitch-adaptive time-frequency smoothing and an instantaneous-frequency-based F0 extraction: Possible role of a repetitive structure in sounds , 1999, Speech Commun..