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首页> 外文期刊>IEEE transactions on audio, speech and language processing >Feature Vector Selection and Use With Hidden Markov Models to Identify Frequency-Modulated Bioacoustic Signals Amidst Noise
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Feature Vector Selection and Use With Hidden Markov Models to Identify Frequency-Modulated Bioacoustic Signals Amidst Noise

机译:特征向量的选择以及与隐马尔可夫模型的结合用于识别噪声中的调频生物声信号

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摘要

This paper describes an effective process for automated detection and classification of frequency-modulated sounds from birds, crickets, and frogs that have a narrow short-time frequency bandwidth. An algorithm is provided for extracting these sign
机译:本文介绍了一种有效的方法,用于自动检测和分类来自短时频带宽较窄的鸟类,和青蛙的调频声音。提供了用于提取这些符号的算法

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