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
Original language | English |
---|---|
Article number | 5373813 |
Pages (from-to) | 2377-2384 |
Number of pages | 8 |
Journal | IEEE Transactions on Consumer Electronics |
Volume | 55 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2009 Nov |
Bibliographical note
Funding Information:1This work was supported by the Korea Research Foundation (KRF) grant funded by the Korea government (MEST) (No. 2009-0077392). It was also supported by the MKE (The Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) support program supervised by the NIPA (National IT Industry Promotion Agency) (NIPA-2009-C1090-0902-0007).
Keywords
- Dynamic time warping
- Gaussian mixture model
- Hidden Markov model
- Keyword recognition
- Speaker recognition
- Vector quantization
- Voice trigger
ASJC Scopus subject areas
- Media Technology
- Electrical and Electronic Engineering