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A Voice Trigger System using Keyword and Speaker Recognition for Mobile Devices

Authors
Lee, HyeopwooChang, SukmoonYook, DongsukKim, Yongserk
Issue Date
11월-2009
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Voice trigger; keyword recognition; speaker recognition; dynamic time warping; vector quantization; Gaussian mixture model; hidden Markov model
Citation
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, v.55, no.4, pp.2377 - 2384
Indexed
SCIE
SCOPUS
Journal Title
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS
Volume
55
Number
4
Start Page
2377
End Page
2384
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/118992
DOI
10.1109/TCE.2009.5373813
ISSN
0098-3063
Abstract
Voice activity detection plays an important role for an efficient voice interface between human and mobile devices, since it can be used as a trigger to activate an automatic speech recognition module of a mobile device. If the input speech signal can be recognized as a predefined magic word coming from a legitimate user, it can be utilized as a trigger. In this paper, we propose a voice trigger system using a keyword-dependent speaker recognition technique. The voice trigger must be able to perform keyword recognition, as well as speaker recognition, without using computationally demanding speech recognizers to properly trigger a mobile device with low computational power consumption. We propose a template based method and a hidden Markov model (HMM) based method for the voice trigger to solve this problem. The experiments using a Korean word corpus show that the template based method performed 4.1 times faster than the HMM based method However, the HMM based method reduced the recognition error by 27.8% relatively compared to the template based method The proposed methods are complementary and can be used selectively depending on the device of interest.(1)
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