Titlebook: Computational Models of Speech Pattern Processing; Keith Ponting Book 1999 Springer-Verlag Berlin Heidelberg 1999 Dialogue systems.Human s

Ejaculate

https://doi.org/10.1007/978-3-030-36592-9ludes the hidden Markov model (HMM) as a special case. The overview gives options for modeling assumptions in terms of correlation structure and parameter tying and outlines the extensions to HMM recognition and training algorithms needed to handle segment models.

thwart

K-Nearest Neighbours Estimator in a HMM-Based Recognition System,n assessed on a frame by frame phonetic identification on the TIMIT database. Thereafter, a method to integrate the K-NN pdf estimator in a HMM-based system is proposed and tested on an acoustic-phonetic decoding task.

石墨

Application of Acoustic Discriminative Training in an Ergodic HMM for Speaker Identification,s and transitions, are defined. We design speaker templates by the combination of four single state HMMs into a four state HMM after re-estimation of the transition probabilities. Experiments conducted with two databases are reported, and the results show that this architecture performs better than others without phonetic classification.

Mettle

Comparison of Several Compensation Techniques for Robust Speaker Verification,derably. In this paper, different techniques which make a speaker verification system more robust against noise are described and compared. Some of these techniques have already been successfully applied in Robust Speech Recognition, and our preliminary results show that they are also very encouraging for Robust Speaker Verification.

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Optometrist

挫敗

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