Suppression of Late Reverberation Effect on Speech Signal Using Long-Term Multiple-step Linear Prediction

Abstract

Abstract-A speech signal captured by a distant microphone is generally smeared by reverberation, which severely degrades automatic speech recognition (ASR) performance. One way to solve this problem is to dereverberate the observed signal prior to ASR. In this paper, a room impulse response is assumed to consist of three parts: a direct-path response, early reflections and late reverberations. Since late reverberations are known to be a major cause of ASR performance degradation, this paper focuses on dealing with the effect of late reverberations. The proposed method first estimates the late reverberations using long-term multi-step linear prediction, and then reduces the late reverberation effect by employing spectral subtraction. The algorithm provided good dereverberation with training data corresponding to the duration of one speech utterance, in our case, less than 6 s. This paper describes the proposed framework for both single-channel and multichannel scenarios. Experimental results showed substantial improvements in ASR performance with real recordings under severe reverberant conditions.

A reverberation-time-aware DNN approach leveraging spatial information for microphone array dereverberation

“…While for DNNSpatial, a 10-frame context window was utilized (i.e., 2 i=1 (2d i + 1) = 10), to ensure a fair comparison and a controlled environment. The possible configurations for feature selection in DNNSpatial are (9, 1), (7,3), and (5, 5). Specifically, (9, 1) implies the number of frames in acoustic context for the first and second microphone is 9 and 1, respectively (i.e., d 1 = 4, d 2 = 0).…”

“…This propagation results in a signal attenuation and spectral distortion, called reverberation, that seriously degrades speech quality and intelligibility. Many dereverberation techniques have thus been proposed in the past (e.g., [1][2][3][4][5]). One direct way is to estimate an inverse filter of the room impulse response *Correspondence: mlyang@xidian.edu.cn 1 National Laboratory of Radar Signal Processing, Xidian University, Xi'an, China Full list of author information is available at the end of the article (RIR) [6] to deconvolve the reverberant signal.…”

“…The RIR can also be varying in time and hard to estimate [7]. Kinoshita et al [3] estimated the late reverberations using long-term multi-step linear prediction, and then reduced the late reverberation effect by employing spectral subtraction.…”

Dereverberation Based on Spectral Subtraction by Multi-channel LMS Algorithm for Hands-free Speech Recognition

“…However, the drawback of this approach is that the optimum parameters for spectral subtraction are empirically estimated from a development dataset and the late reverberation cannot be subtracted well since it is not modeled precisely. [18] proposed a novel dereverberation method utilizing multi-step forward linear prediction. They estimated the linear prediction coefficients in a time domain and suppressed the amplitude of late reflections through spectral subtraction in a spectral domain.…”

“…This enables us to treat the late reverberation as additive noise, and a noise reduction technique based on spectral subtraction can be easily applied to compensate for the late reverberation. By excluding the phase information from the dereverberation operation, the dereverberation reduction in a power spectral domain provides robustness against certain errors that the conventional sensitive inverse filtering method cannot achieve [18]. The compensation parameter (that is, the spectrum of the impulse response) for spectral subtraction is required.…”