Rectified linear unit can assist griffin-lim phase recovery

Kohei Yatabe, Yoshiki Masuyama, Yasuhiro Oikawa

    研究成果: Conference contribution

    8 被引用数 (Scopus)

    抄録

    Phase recovery is an essential process for reconstructing a time-domain signal from the corresponding spectrogram when its phase is contaminated or unavailable. Recently, a phase recovery method using deep neural network (DNN) was proposed, which interested us because the inverse short-time Fourier transform (inverse STFT) was utilized within the network. This inverse STFT converts a spectrogram into its time-domain counterpart, and then the activation function, leaky rectified linear unit (ReLU), is applied. Such nonlinear operation in time domain resembles the speech enhancement method called the harmonic regeneration noise reduction (HRNR). In HRNR, a time-domain nonlinearity, typically ReLU, is applied for assistance in enhancing the higher-order harmonics. From this point of view, one question arose in our mind: Can time-domain ReLU solely assist phase recovery? Inspired by this curious connection between the recent DNN-based phase recovery method and HRNR in speech enhancement, the ReLU assisted Griffin-Lim algorithm is proposed in this paper to investigate the above question. Through an experiment of speech denoising with the oracle Wiener filter, some positive effect of the time-domain nonlinearity is confirmed in terms of the scores of the short-time objective intelligibility (STOI).

    本文言語English
    ホスト出版物のタイトル16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018 - Proceedings
    出版社Institute of Electrical and Electronics Engineers Inc.
    ページ555-559
    ページ数5
    ISBN(電子版)9781538681510
    DOI
    出版ステータスPublished - 2018 11 2
    イベント16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018 - Tokyo, Japan
    継続期間: 2018 9 172018 9 20

    Other

    Other16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018
    CountryJapan
    CityTokyo
    Period18/9/1718/9/20

    ASJC Scopus subject areas

    • Signal Processing
    • Acoustics and Ultrasonics

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