Paper Info
Title
Prosodic Features-Based Speaker Verification Using Speaker-Specific-Text For Short Utterances
Abstract
Over the past several years, Gaussian mixture model and its variants have been dominant architectures in text-independent and text-dependent speaker recognition field. The recognition accuracy of above-mentioned models declines when experimental utterances' length becomes short in practical application. Presently, Mel-frequency cepstral coefficients are generally used to characterise the properties of the vocal tract and widely applied in speech recognition. In addition, prosodic features, such as pitch and formant, are generally considered to describe the glottal characteristics. However, the efficiency of those approaches remains unsatisfactory. In text-dependent short utterance speaker verification systems, prosodic features can assist to improve the recognition result theoretically. In order to optimise the performance of speaker verification systems under the framework of adapted GMM-UBM, we adopt a variant speaker verification system based on prosodic features, in which a dual judgement mechanism is used in order to integrate vocal tract features with prosodic features. Experimental results showed that the new speech recognition system gives a better consequence.
Year
DOI
Venue
2017
10.1504/IJES.2017.10005717
INTERNATIONAL JOURNAL OF EMBEDDED SYSTEMS
Keywords
Field
DocType
speaker verification, text dependent, prosodic features, dual judgement mechanism
Speaker verification,Mel-frequency cepstrum,Computer science,Utterance,Speech recognition,Speaker recognition,Speaker diarisation,Natural language processing,Artificial intelligence,Formant,Vocal tract,Mixture model
Journal
Volume
Issue
ISSN
9
3
1741-1068
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Jianwu Zhang1187.11
Jianchao He200.68
Zhendong Wu39114.16
Freeha Azmat492.28
Ping Li57814.22