This paper considers the enhancement of noisy speech. Earlier studies have revealed that an approach that enhances spectral envelopes by using prior knowledge about the all-pole (AP) model parameters of clean speech learnt from speech corpora is advantageous in terms of the amount of musical noise and speech distortion. This paper proposes a new speech enhancement method, in which harmonic structure enhancement is incorporated in learning-based spectral envelope enhancement to further improve performance. The harmonic structure is represented by using a harmonic Gaussian mixture model (GMM), which is parameterized by a voicing indicator and a fundamental frequency. The parameters of the AP model and the harmonic GMM are jointly estimated by maximum a posteriori estimation, thus enabling the enhancement of spectral envelopes and harmonic structures in a unified framework. The proposed method outperforms the spectral envelope enhancement approach by 0.85 dB in cepstral distance.
|ホスト出版物のタイトル||ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings|
|出版ステータス||Published - 2010|
|イベント||2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, TX|
継続期間: 2010 3月 14 → 2010 3月 19
|Other||2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010|
|Period||10/3/14 → 10/3/19|
ASJC Scopus subject areas