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Titlebook: Multi-Pitch Estimation; Mads Græsbøll Christensen,Andreas Jakobsson Book 2009 Springer Nature Switzerland AG 2009

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发表于 2025-3-21 19:49:45 | 显示全部楼层 |阅读模式
书目名称Multi-Pitch Estimation
编辑Mads Græsbøll Christensen,Andreas Jakobsson
视频video
丛书名称Synthesis Lectures on Speech and Audio Processing
图书封面Titlebook: Multi-Pitch Estimation;  Mads Græsbøll Christensen,Andreas Jakobsson Book 2009 Springer Nature Switzerland AG 2009
描述Periodic signals can be decomposed into sets of sinusoids having frequencies that are integer multiples of a fundamental frequency. The problem of finding such fundamental frequencies from noisy observations is important in many speech and audio applications, where it is commonly referred to as pitch estimation. These applications include analysis, compression, separation, enhancement, automatic transcription and many more. In this book, an introduction to pitch estimation is given and a number of statistical methods for pitch estimation are presented. The basic signal models and associated estimation theoretical bounds are introduced, and the properties of speech and audio signals are discussed and illustrated. The presented methods include both single- and multi-pitch estimators based on statistical approaches, like maximum likelihood and maximum a posteriori methods, filtering methods based on both static and optimal adaptive designs, and subspace methods based on the principles of subspace orthogonality and shift-invariance. The application of these methods to analysis of speech and audio signals is demonstrated using both real and synthetic signals, and their performance is as
出版日期Book 2009
版次1
doihttps://doi.org/10.1007/978-3-031-02558-7
isbn_softcover978-3-031-01430-7
isbn_ebook978-3-031-02558-7Series ISSN 1932-121X Series E-ISSN 1932-1678
issn_series 1932-121X
copyrightSpringer Nature Switzerland AG 2009
The information of publication is updating

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发表于 2025-3-21 22:43:39 | 显示全部楼层
1932-121X lem of finding such fundamental frequencies from noisy observations is important in many speech and audio applications, where it is commonly referred to as pitch estimation. These applications include analysis, compression, separation, enhancement, automatic transcription and many more. In this book
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Book 2009 based on both static and optimal adaptive designs, and subspace methods based on the principles of subspace orthogonality and shift-invariance. The application of these methods to analysis of speech and audio signals is demonstrated using both real and synthetic signals, and their performance is as
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Synthesis Lectures on Speech and Audio Processinghttp://image.papertrans.cn/n/image/640003.jpg
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