NDLI: On the Studies of Syllable Segmentation and Improving MFCCs for Automatic Birdsong Recognition

Content Provider	IEEE Xplore Digital Library
Author	Chih-Hsun Chou Pang-Hsin Liu Bingjing Cai
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Sci. & Inf. Eng., Chung Hua Univ., Hsinchu (Chih-Hsun Chou; Pang-Hsin Liu) \|\| Sch. of Software, Yunnan Univ., Kunming (Bingjing Cai)
Abstract	Birdsongs are typically divided into four hierarchical levels: note, syllable, phrase, and song, of which syllable plays an important role in bird species recognition. To improve the recognition rate of birdsongs, in this study an enhanced syllable segmentation method based on R-S endpoint detection method was presented. Furthermore, a decision based neural network with suitable reinforcement learning rule was developed as the classifier. The proposed methods combined with the well-known MFCCs feature vector form a birdsong recognition system that was applied to two recognition problems: one is the recognition of a set of arbitrary syllables and the other is the recognition of a section of a birdsong. Experimental results show the performances of the proposed methods.
Starting Page	745
Ending Page	750
File Size	264281
Page Count	6
File Format	PDF
ISBN	9780769534732
DOI	10.1109/APSCC.2008.6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-09
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	syllable segmentation Mel-frequency cepstral coefficients Time domain analysis Birds Birdsong recognition Frequency domain analysis Learning Support vector machines decision based neural network Neural networks Hidden Markov models Cepstrum Support vector machine classification Prototypes
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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