MULTI-MICROPHONE METHOD FOR ESTIMATION OF TARGET AND NOISE SPECTRAL VARIANCES FOR SPEECH DEGRADED BY REVERBERATION AND OPTIONALLY ADDITIVE NOISE

摘要

The application relates to an audio processing system and a method of processing a noisy (e.g. reverberant) signal comprising first (v) and optionally second (w) noise signal components and a target signal component (x), the method comprising a) Providing or receiving a time-frequency representation Yi(k,m) of a noisy audio signal yi at an ith input unit, i=1, 2, . . . , M, where M≧2; b) Providing (e.g. predefined spatial) characteristics of said target signal component and said noise signal component(s); and c) Estimating spectral variances or scaled versions thereof λV, λX of said first noise signal component v (representing reverberation) and said target signal component x, respectively, said estimates of λV and λX being jointly optimal in maximum likelihood sense, based on the statistical assumptions that a) the time-frequency representations Yi(k,m), Xi(k,m), and Vi(k,m) (and Wi(k,m)) of respective signals yi(n), and signal components xi and vi (and wi) are zero-mean, complex-valued Gaussian distributed, b) that each of them are statistically independent across time m and frequency k, and c) that Xi(k,m) and Vi(k,m) (and Wi(k,m)) are uncorrelated. An advantage of the invention is that it provides the basis for an improved intelligibility of an input speech signal. The invention may e.g. be used for hearing assistance devices, e.g. hearing aids.

主权项

1. A method of processing a noisy audio signal y(n) comprising a target signal component x(n) and a first noise signal component v(n), n representing time, the method comprising
a) Providing or receiving a time-frequency representation Yi(k,m) of the noisy audio signal yi(n) at an ith input unit, i=1, 2, . . . , M, where M is larger than or equal to two, in a number of frequency bands and a number of time instances, k being a frequency band index and m being a time index; b) Providing characteristics of said target signal component and said first noise signal component; and c) Estimating spectral variances or scaled versions thereof λV, λX of said first noise signal component v and said target signal component x, respectively, as a function of frequency index k and time index m, said estimates of λV and λX being jointly optimal in maximum likelihood sense, based on the statistical assumptions that a) the time-frequency representations Yi(k,m), Xi(k,m), and Vi(k,m) of respective signals yi(n), and signal components xi(n), and vi(n) are zero-mean, complex-valued Gaussian distributed, b) that each of them are statistically independent across time m and frequency k, and c) that Xi(k,m) and Vi(k,m) are uncorrelated.