Signal Processing Methods for Music TranscriptionAnssi Klapuri, Manuel Davy Springer Science & Business Media, 26/02/2007 - 440 páginas Signal Processing Methods for Music Transcription is the first book dedicated to uniting research related to signal processing algorithms and models for various aspects of music transcription such as pitch analysis, rhythm analysis, percussion transcription, source separation, instrument recognition, and music structure analysis. Following a clearly structured pattern, each chapter provides a comprehensive review of the existing methods for a certain subtopic while covering the most important state-of-the-art methods in detail. The concrete algorithms and formulas are clearly defined and can be easily implemented and tested. A number of approaches are covered, including, for example, statistical methods, perceptually-motivated methods, and unsupervised learning methods. The text is enhanced by a common reference and index. |
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... spectrogram , as well as a time and time - lag represen- tation called cepstral representation ; see Section 2.1.3 . The following section discusses some basic properties of Fourier Transforms . 2.1.1 The Fourier Transform The frequency ...
... spectrogram , defined as the Fourier transform of successive signal frames.3 Frames are widely used in audio processing algorithms . They are portions of the signal with given time localizations . More precisely , the frame localized at ...
... spectrogram with good time resolution and bad frequency resolution , whereas a longer window leads to the opposite situa- tion.5 Figure 2.2 represents two spectrograms of a piano excerpt , illustrating the influence of the window length ...
... Spectrograms of a piano excerpt computed with Hamming windows with length 20 ms ( left ) and 80 ms ( right ) . The ... spectrogram is ob- tained by using ( t , f ) = WVw ( t , f ) ; that is , SP ( t , f ) = t , f [ WV x * WVw ] ( t , f ) ...
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Índice
17 | |
21 | |
Sparse Adaptive Representations for Musical Signals | 65 |
Stephen Hainsworth | 101 |
Unpitched Percussion Transcription | 130 |
Automatic Classification of Pitched Musical Instrument | 163 |
Multiple Fundamental Frequency Estimation Based | 203 |
Auditory ModelBased Methods for Multiple Fundamental | 228 |
Unsupervised Learning Methods for Source Separation | 267 |
Auditory Scene Analysis in Music Signals | 298 |
Music Scene Description | 327 |
Singing Transcription | 360 |
References | 391 |
Index | 429 |
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Signal Processing Methods for Music Transcription Anssi Klapuri,Manuel Davy Pré-visualização indisponível - 2010 |