DocumentCode :
3723893
Title :
Exploration of vowel onset and offset points for hybrid speech segmentation
Author :
Biswajit Dev Sarma;Bidisha Sharma;S. Aswin Shanmugam;S. R. Mahadeva Prasanna;Hema A. Murthy
Author_Institution :
Department of Electronics and Electrical Engineering, Indian Institute of Technology Guwahati, 781039, India
fYear :
2015
Firstpage :
1
Lastpage :
6
Abstract :
Automatic segmentation of speech using embedded reestimation of monophone hidden Markov models (HMMs) followed by forced alignment may not give accurate boundaries. Group delay (GD) processing for refining the boundaries at the syllable level is attempted earlier. This paper aims at exploring vowel onset point (VOP) and vowel offset or end point (VEP) for correcting the boundaries obtained using HMM alignment. HMM models the class information well, however may not detect the exact boundary. In case of VOPs and VEPs, spurious rate or miss rate can be there, but detected boundaries are more accurate. Combining both HMM and VOP/VEP gives improvement in terms of log likelihood scores of forced aligned phoneme boundaries. HMM boundaries are corrected using VOP/VEP and model parameters are reestimated at the syllable level. Results are compared with that of GD based correction and found that overall performance is comparable. Performance for vowels is found to be higher than that of GD based refinement as the refinement in this case is mainly at the vowel boundaries. HMM based speech synthesis systems (HTS) are developed using phone as a basic unit with the proposed segmentation method. Subjective evaluation indicates that there is an improvement in the quality of synthesis.
Keywords :
"Hidden Markov models","Speech","Delays","Speech synthesis","Force","Speech enhancement"
Publisher :
ieee
Conference_Titel :
TENCON 2015 - 2015 IEEE Region 10 Conference
ISSN :
2159-3442
Print_ISBN :
978-1-4799-8639-2
Electronic_ISBN :
2159-3450
Type :
conf
DOI :
10.1109/TENCON.2015.7373137
Filename :
7373137
Link To Document :
بازگشت