A Voice Trigger System using Keyword and Speaker Recognition for Mobile Devices
- Authors
- Lee, Hyeopwoo; Chang, Sukmoon; Yook, Dongsuk; Kim, 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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Collections - Graduate School > Department of Computer Science and Engineering > 1. Journal Articles
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