5Projects on the acoustic monitoring of animals in natural habitats generally face the problem of managing extensive amounts of data, both needed for-and produced by-observation or experimentation. While there are many publicly accessible databases for recordings themselves, we are aware of none for annotated song sequences. In this paper, we describe our database system of bird vocalizations and introduce our online sample repository for the community of researchers studying the syntax of bird song.
In this paper, we present a series of experiments on the automated classification of Cassin's Vireo individuals from song phrases using support vector machines and from sequences of song phrases using hidden Markov models. Experimental results show that accurate classification of bird individuals can be achieved using these two different levels of description of bird songs.
In this paper, we present a comparative study on the application of pattern recognition algorithms to the identification of bird individuals from their song. A collection of experiments on the supervised classification of Cassin's Vireo individuals were conducted to identify the algorithm that produced the highest classification accuracy. Preliminary results indicated that Multinomial Naive Bayes produced excellent classification of bird individuals.
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