NDLI: An automatic speaker-speech recognition system for friendly HMI based on binary halved clustering

Content Provider	IEEE Xplore Digital Library
Author	Chih-Hsiang Peng Chih-Hung Chou Ta-Wen Kuan Po-Chuan Lin Jhing-Fa Wang Pen-Yuan Yu
Copyright Year	2014
Description	Author affiliation: Dept. of Digital Game & Animation Design, Tung-Fang Design Inst., Kaohsiung, Taiwan (Po-Chuan Lin) \|\| Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan (Chih-Hsiang Peng; Chih-Hung Chou; Ta-Wen Kuan; Jhing-Fa Wang; Pen-Yuan Yu)
Abstract	This work presents a low-cost and fast-trainable automatic speaker-speech recognition (ASSR) system, by proposed binary halved clustering (BHC) method for human-machine interface (HMI) on an embedded platform, owing to the trait of low cost in ASSR system is essential and affordable for real-world application. In addition, fast-trainable ability can provide fast responding time. The reduction of waiting time makes the proposed HMI to be friendly for users. The speech recognition uses enhanced cross-word reference templates (ECWRTs) for template training type. The novel BHC method uses binary-halved splitting to generate speaker models for low complexity requirement. The regularity of binary halved behavior is beneficial for data scheduling and resource sharing in the embedded ASSR system. Compared with the conventional works, simulation results indicate that the proposed hardware accelerator achieves 28% less cost, 90% less responding time, an ASSR accuracy of 90%. Comparison exhibits that performance of the proposed system is greater than the conventional works, thereby demonstrating the friendly and affordable factor of the proposed HMI.
Starting Page	161
Ending Page	164
File Size	343984
Page Count	4
File Format	PDF
ISBN	9781479962846
DOI	10.1109/ICOT.2014.6956624
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Support vector machines Embedded systems Human-machine interface (HMI) Embedded system Automatic speaker-speech recognition (ASSR) Hidden Markov models Speech recognition Speech Enhanced cross-word reference templates (ECWRTs) Testing Binary halved clustering (BHC)
Content Type	Text
Resource Type	Article

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