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Non-Negative Temporal Decomposition Regularization With an Augmented Lagrangian

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Ramirez, Miguel Arjona
Número total de Autores: 1
Tipo de documento: Artigo Científico
Fonte: IEEE SIGNAL PROCESSING LETTERS; v. 23, n. 5, p. 663-667, MAY 2016.
Citações Web of Science: 0

Non-negative matrix factorization (NMF) has recently been applied to temporal decomposition (TD) of speech spectral envelopes represented by line spectral frequencies. A couple of inherent TD constraints, which are otherwise handled as ad hoc exceptions, has also been incorporated using NMF, including line spectral frequency (LSF) ordering and monotonic event functions. Here, these constraints are analyzed and a third inherent constraint is incorporated into an NMF analysis. This is the complementarity in the sense that two overlapping event functions uniformly add up to one, which has been handled, at best, by a quadratic penalty term. We propose the use of an augmented Lagrangian including a term with the Lagrange multipliers (LMs). Additionally, a multiplicative update rule for the LMs is proposed, which fits nicely into the nature of NMF updates. Further, previous difficulties with nonsmooth spectral envelopes have been resolved by obtaining the spectral envelopes from TANDEM-STRAIGHT spectrograms. Good results are reached at the tight event rate of 12.3 ev/s, featuring mean log-spectral distortions ranging from 1.2 dB to about 1.5 dB depending on the regularizations. (AU)

Processo FAPESP: 12/24789-0 - Análise de sinais de áudio e voz para reconstrução e reconhecimento
Beneficiário:Miguel Arjona Ramírez
Linha de fomento: Auxílio à Pesquisa - Regular
Processo FAPESP: 15/25512-0 - Análise Condicional para Codificação e Reconhecimento de Sinais de Áudio e Voz
Beneficiário:Miguel Arjona Ramírez
Linha de fomento: Auxílio à Pesquisa - Regular