Enhanced energy redistribution speech intelligibility algorithm with real-time implementation
Manasa Raghavan, Mark D. Skowronski, John G. Harris · The Journal of the Acoustical Society of America · 2004
Speech intelligibility enhancement is a concern for mobile platforms operating in noisy environments. Current noise-reduction techniques, such as subspace methods and spectral subtraction, operate on speech corrupted by acoustic and transmission noise. Yet preprocessing techniques, which operate on clean speech before noise corruption, have received little attention. Previously, the authors have developed the energy redistribution algorithm [J. Acoust. Soc. Am. 112, 2305 (2002)], which, based on characteristics of clear speech as well as the Lombard effect, redistributes energy in time from voiced regions to unvoiced regions of speech. The algorithm is designed efficiently for real-time implementation, and in this work the algorithm is demonstrated on a mobile platform, TIs TMS320C6713 DSK board. Furthermore, two enhancements to the algorithm are introduced: (1) a variable unvoiced gain factor and (2) a high pass filter (HPF). The variable unvoiced gain factor adjusts the amount of energy redistributed, and the HPF, a compact algorithm shown previously to enhance clean speech in noisy environments [Niederjohn and Grotelueschen, IEEE Trans. Acoust., Speech, Signal Process. 24(5), 277–282 (1976)], is tested on sentences from the Hearing in Noise Test (HINT) corrupted by speech-shaped noise. Results show improved speech intelligibility for both enhancements.