The Analysis of Identification of Cetaceans’ Whistle With Support Vector Machine
Date Issued
2014
Date
2014
Author(s)
Lai, Ying-Chung
Abstract
Whales and dolphins use the whistle to identify cetacean species characteristics, whether in Taiwan or abroad study mostly cetaceans whistle when using frequency map (spectrogram) on the basis of characteristics to develop, and supplemented by professional artificial identification. By listening to the sound samples, then compared the visual signal when the frequency diagram (spectrogram). However, due to different types of whales and dolphins whistle which looks very similar, can not be directly judged by the naked eye whistle to whistle which cetacean.
Therefore, this study is a way to simulate human auditory characteristics to identify the characteristics of cetacean whistle, capture technology is based on the characteristics of auditory perceptual characteristics
Finally, the classification of the way we use the support vector machine (SVM).
Support vector machine (SVM) is a new kind of machine learning method based on statistical learning theory Vapnik proposed
Preliminary experimental results show that this paper proposed approach for the identification of whales and dolphins whistle quite a significant rate increase, after hoping to enhance recognizable again, whistle cetacean research for the future will be an indispensable tool
Subjects
支持向量機
梅爾倒頻譜係數
鯨豚哨音
Type
thesis
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