Title: TREND TYING IN THE SEGMENTAL-FEATURE HMM

Authors: Young-Sun Yun

Abstract: We present the reduction method of number of parameters in segmental-feature HMM (SFHMM). If the SFHMM shows better results than CHMM, the number of parameters is greater than that of CHMM. Therefore, there is a need for new approach that reduces the number of parameters. In general, trajectory can be separated by the trend and location. Since the trend means the variation of segmental features and occupies the large portion of SFHMM, if the trend is shared, the number of parameters of SFHMM maybe decreases. The proposed method shares the trend part of trajectories by quantization. The experiments are performed on TIMIT corpus to examine the effectiveness of the trend tying. The experimental results show that its performance is the almost same to that of previous studies. To obtain the better results with small amount of parameters, the various conditions for the trajectory components must be considered.

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