Foreground Speech Segmentation and Enhancement Using Glottal Closure Instants and Mel Cepstral Coefficients

• Published in: IEEE/ACM transactions on audio, speech, and language processing Vol. 24; no. 7; pp. 1205 - 1219
• Main Authors: Deepak, K. T., Mahadeva Prasanna, S. R.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.07.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acoustics; Background noise; Closures; Foreground segmentation; glottal closure instants; Mathematical models; MCC; Microphones; MLSA; Noise measurement; Segmentation; Signal to noise ratio; Spectra; Speech; Speech disorders; Speech enhancement; State of the art; zero band filter; Foreground segmentation; zero band filter; MLSA; glottal closure instants; MCC; speech enhancement
• ISSN: 2329-9290; 2329-9304
• DOI: 10.1109/TASLP.2016.2549699

In this paper, the speech signal recorded from the desired speaker close to microphone in natural environment is regarded as foreground speech and rest of the interfering sources as background noise . The proposed paper exploits speech production features like glottal closure instants in time domain and vocal tract information in spectral domain to segment the desired speaker's speech and to further enhance it. The foreground speech is perceptually enhanced using the auditory perception feature in mel-frequency domain using mel-cepstral coefficients and its inversion using mel log spectrum approximation filter. The focus is on enhancing the production and perceptual features of foreground speech rather than relying on modeling the interfering sources. The speech data are collected in different natural environments from different speakers in order to evaluate the proposed method. The enhanced speech signals derived at three different stages of the proposed method are evaluated with state-of-the-art methods in terms of subjective and objective measures. The proposed method provides improved performance compared to the considered state-of-the-art methods. In terms of the proposed objective measure foreground to background Ratio, the enhancement approach presented in this paper gives an average improvement of 12 dB as opposed to existing spectral subtraction-based method which provides 3 dB. Moreover, subjective evaluation using 24 different subjects corroborates the objective test results.