Abstract
This paper addresses the problem of blind speech dereverberation by inverse filtering of a room acoustic system. Since a speech signal can be modeled as being generated by a speech production system driven by an innovations process, a reverberant signal is the output of a composite system consisting of the speech production and room acoustic systems. Therefore, we need to extract only the part corresponding to the room acoustic system (or its inverse filter) from the composite system (or its inverse filter). The time-variant nature of the speech production system can be exploited for this purpose. In order to realize the time-variance-based inverse filter estimation, we introduce a joint estimation of the inverse filters of both the time-invariant room acoustic and the time-variant speech production systems, and present two estimation algorithms with distinct properties.
Highlights
Room reverberation degrades speech intelligibility or corrupts the characteristics inherent in speech
We made signals of various lengths by concatenating his or her utterances. These signals were used as the source signals, and by using these signals, we could investigate the dependence of the performance on the signal length
We have described the problem of speech dereverberation
Summary
Room reverberation degrades speech intelligibility or corrupts the characteristics inherent in speech. The observed signal (reverberant signal) is the output of the system driven by the source signal (clean speech signal). The source signal is modeled as being generated by a time variant autoregressive (AR) system corresponding to an articulatory filter driven by an innovations process [1]. For the sake of definiteness, the AR system corresponding to the articulatory filter and the system corresponding to the room’s signal transmission channel are refered to as the speech production system and the room acoustic system, respectively. The observed signal is the output of the composite system of the speech production and room acoustic systems driven by the innovations process. In order to estimate the source signal, the dereverberation may require the inverse filter of the room acoustic system. Blind speech dereverberation involves the estimation of the inverse filter of the room acoustic system separately from that of the speech production system under the condition that neither the parameters of the speech production system nor those of the room acoustic system are available
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