BIRDSONG ANALYSIS USING BETA PROCESS HIDDEN MARKOV MODEL

被引：0

作者：

Hamada, Ryunosuke ^{[1
]}

Kubo, Takatomi ^{[1
,2
]}

Katahira, Kentaro ^{[2
]}

Suzuki, Kenta ^{[2
]}

Okanoya, Kazuo ^{[2
]}

Ikeda, Kazushi ^{[1
]}

机构：

[1] Nara Inst Sci & Technol, 8916-5 Takayama, Ikoma, Nara 6300192, Japan

[2] RIKEN, Brain Sci Inst, Wako, Saitama 3510198, Japan

来源：

2014 IEEE INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP) | 2014年

关键词：

Birdsongs; Syntactic rule; Automatic annotation; Bayesian nonparametrics; Beta process hidden Markov model;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We proposed a new scheme on automatic annotation and analysis for songs of Bengalese finches, that have variability in terms of syllable sequencing. The scheme annotates songs by using the beta process hidden Markov model, a Bayesian non-parametrics method. The annotation was confirmed to agree to the results by the manual annotation by an expert almost perfectly (0.81-1.00) for songs by three out of four Bengalese finches. Our scheme also analyzed the syntactic rules of the birdsongs and found that the difference of the variations in sequencing of four different birds was accounted for by the difference of tutors, giving a new insight to development of syntax.

引用

页数：5

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