title: Reconstruction techniques for improving the perceptual quality of binary masked speech.
abstract: This study proposes an approach to improve the perceptual quality of speech separated by binary masking through the use of reconstruction in the time-frequency domain. Non-negative matrix factorization and sparse reconstruction approaches are investigated, both using a linear combination of basis vectors to represent a signal. In this approach, the short-time Fourier transform (STFT) of separated speech is represented as a linear combination of STFTs from a clean speech dictionary. Binary masking for separation is performed using deep neural networks or Bayesian classifiers. The perceptual evaluation of speech quality, which is a standard objective speech quality measure, is used to evaluate the performance of the proposed approach. The results show that the proposed techniques improve the perceptual quality of binary masked speech, and outperform traditional time-frequency reconstruction approaches.
authors.affiliation: Department of Computer Science and Engineering, The Ohio State University, Columbus, Ohio 43210.
authors.forename: Donald S
authors.initials: DS
authors.lastname: Williamson
authors.affiliation: Department of Computer Science and Engineering, The Ohio State University, Columbus, Ohio 43210.
authors.forename: Yuxuan
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Department of Computer Science and Engineering and the Center for Cognitive and Brain Sciences, The Ohio State University, Columbus, Ohio 43210.
authors.forename: DeLiang
authors.initials: D
authors.lastname: Wang
mesh_terms: D000161:Acoustic Stimulation; D000465:Algorithms; D001302:Audiometry, Speech; D001499:Bayes Theorem; D005583:Fourier Analysis; D006801:Humans; D016014:Linear Models; D016571:Neural Networks, Computer; D009622:Noise / Q000009:adverse effects*; D010470:Perceptual Masking; D012815:Signal Processing, Computer-Assisted; D013061:Speech Acoustics; D013065:Speech Intelligibility; D013067:Speech Perception; D013068:Speech Production Measurement; D013997:Time Factors; D014833:Voice Quality
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