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Ganseman et al., 2012 - Google Patents
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Ganseman et al., 2012 - Google Patents

Improving plca-based score-informed source separation with invertible constant-q transforms

Ganseman et al., 2012

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Document ID
4680289768446084776
Author
Ganseman J
Scheunders P
Dixon S
Publication year
Publication venue
2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO)

External Links

Snippet

Probabilistic Latent Component Analysis is a widely adopted variant of Nonnegative Matrix Factorization for the purpose of single channel audio source separation. It has seen many extensions, including incorporation of prior information derived from music scores. Recent …
Continue reading at new.eurasip.org (PDF) (other versions)

Classifications

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    • G10L21/00Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/003Changing voice quality, e.g. pitch or formants
    • G10L21/007Changing voice quality, e.g. pitch or formants characterised by the process used
    • G10L21/013Adapting to target pitch
    • G10L2021/0135Voice conversion or morphing
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    • G10L21/00Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208Noise filtering
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    • G10L21/00Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/038Speech enhancement, e.g. noise reduction or echo cancellation using band spreading techniques
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    • G10MUSICAL INSTRUMENTS; ACOUSTICS
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    • G10L25/03Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 characterised by the type of extracted parameters
    • G10L25/18Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 characterised by the type of extracted parameters the extracted parameters being spectral information of each sub-band
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    • G10L19/00Speech or audio signal analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signal, using source filter models or psychoacoustic analysis
    • G10L19/02Speech or audio signal analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signal, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders
    • GPHYSICS
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    • G10H2210/031Musical analysis, i.e. isolation, extraction or identification of musical elements or musical parameters from a raw acoustic signal or from an encoded audio signal
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    • G10L15/065Adaptation
    • G10L15/07Adaptation to the speaker
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    • GPHYSICS
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    • G10H2250/131Mathematical functions for musical analysis, processing, synthesis or composition
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    • G10H7/08Instruments in which the tones are synthesised from a data store, e.g. computer organs by calculating functions or polynomial approximations to evaluate amplitudes at successive sample points of a tone waveform
    • G10H7/10Instruments in which the tones are synthesised from a data store, e.g. computer organs by calculating functions or polynomial approximations to evaluate amplitudes at successive sample points of a tone waveform using coefficients or parameters stored in a memory, e.g. Fourier coefficients

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