title: Noise reduction combining time-frequency epsilon-filter and M-transform.
abstract: This paper introduces noise reduction combining time-frequency epsilon-filter (TF epsilon-filter) and time-frequency M-transform (TF M-transform). Musical noise is an offensive noise generated due to noise reduction in the time-frequency domain such as spectral subtraction and TF epsilon-filter. It has a deleterious effect on speech recognition. To solve the problem, M-transform is introduced. M-transform is a linear transform based on M-sequence. The method combining the time-domain epsilon-filter (TD epsilon-filter) and time-domain M-transform (TD M-transform) can reduce not only white noise but also impulse noise. Musical noise is isolated in the time-frequency domain, which is similar to impulse noise in the time domain. On these prospects, this paper aims to reduce musical noise by improving M-transform for the time-frequency domain. Noise reduction by using TD M-transform and the TD epsilon-filter is first explained to clarify its features. Then, an improved method applying M-transform to the time-frequency domain, namely TF M-transform, is described. Noise reduction combining the TF epsilon-filter and TF M-transform is also proposed. The proposed method can reduce not only high-level nonstationary noise but also musical noise. Experimental results are also given to demonstrate the performance of the proposed method.
authors.affiliation: Major in Pure and Applied Physics, Waseda University, Tokyo, Japan. tomomi@shalab.phys.waseda.ac.jp
authors.forename: Tomomi
authors.initials: T
authors.lastname: Abe
authors.forename: Mitsuharu
authors.initials: M
authors.lastname: Matsumoto
authors.forename: Shuji
authors.initials: S
authors.lastname: Hashimoto
mesh_terms: D000162:Acoustics; D000465:Algorithms; D006801:Humans; D016014:Linear Models; D008954:Models, Biological; D009146:Music; D009622:Noise; D010470:Perceptual Masking; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D013018:Sound Spectrography; D013067:Speech Perception; D049250:Speech Recognition Software; D013997:Time Factors