• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.85-94
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• 2017

In this paper, I proposed a sound model generation and a most frequent model search algorithm for recognizing animal vocalization. The sound model generation algorithm generates a optimal set of models through repeating processes such as the training process, the Viterbi Search process, and the most frequent model search process while adjusting HMM(Hidden Markov Model) structure to improve global recognition rate. The most frequent model search algorithm searches the list of models produced by Viterbi Search Algorithm for the most frequent model and makes it be the final decision of recognition process. It is implemented using MFCC(Mel Frequency Cepstral Coefficient) for the sound feature, HMM for the model, and C# programming language. To evaluate the algorithm, a set of animal sounds for 27 species were prepared and the experiment showed that the sound model generation algorithm generates 27 HMM models with 97.29 percent of recognition rate.

• Animal cells and systems
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• v.9 no.2
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• pp.47-55
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• 2005

Avian vocalization has been main topics in studying animal communication. The structure and usage as well as development and function of vocalization vary enormously among species and even among populations, and thus we reviewed the general patterns of song learning and the consequences of song communication in birds at the behavioural level: first, we compared the different learning phenomena between non-songbird and songbird, and we investigated the learning process of songbird both in the field and in the lab, which are needed to fully understand vocal communication. Second, we discussed a recent trend of sexual selection hypothesis explaining the structural and functional diversity of song in songbirds with repertoire and presented how the repertoire is actually used between neighbours based on individual recognition.

• Journal of Ecology and Environment
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• v.30 no.1
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• pp.9-15
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• 2007

Black-tailed gulls (Larus crassirostris) produce alarm calls apparently related to their anti-predator behaviors, but the hypothesis that the calls are actually used as functionally referential alarm signals has not yet been tested. In this study, we performed a series of experiments using visual (a stuffed goshawk: Accipiter gentilis) and acoustic (alarm calls and a control vocalization) stimuli at 15 sites in Sinjindo-ri and Dowhang-ri, Taean-gun, Chungnam province to examine anti-predator responses of the gulls to alarm calls in playback trials. We found that the gulls' visual recognition of a perched hawk model in the absence of alarm vocalizations was weak or absent because the model was noticed in only two out of 16 trials. The gulls' responses to playbacks of the alarm call only and the alarm call with a visual stimulus differed from responses to the control vocalization in latency to approach, time mobbing, and the percentage of gulls responding, while the responses to alarm call only differed from alarm call with a visual stimulus in latency to first fly, latency to call, and time mobbing. The results of this study suggest that alarm calls of black-tailed gulls are used to elicit appropriate anti-predator behaviors that are intensified when a predator is detected visually.