Reverberation: models, estimation and application

The use of reverberation models is required in many applications such as acoustic measurements, speech dereverberation and robust automatic speech recognition. The aim of this thesis is to investigate different models and propose a perceptually-relevant reverberation model with suitable parameter estimation techniques for different applications. Reverberation can be modelled in both the time and frequency domain. The model parameters give direct information of both physical and perceptual characteristics. These characteristics create a multidimensional parameter space of reverberation, which can be to a large extent captured by a time-frequency domain model. In this thesis, the relationship between physical and perceptual model parameters will be discussed. In the first application, an intrusive technique is proposed to measure the reverberation or reverberance, perception of reverberation and the colouration. The room decay rate parameter is of particular interest. In practical applications, a blind estimate of the decay rate of acoustic energy in a room is required. A statistical model for the distribution of the decay rate of the reverberant signal named the eagleMax distribution is proposed. The eagleMax distribution describes the reverberant speech decay rates as a random variable that is the maximum of the room decay rates and anechoic speech decay rates. Three methods were developed to estimate the mean room decay rate from the eagleMax distributions alone. The estimated room decay rates form a reverberation model that will be discussed in the context of room acoustic measurements, speech dereverberation and robust automatic speech recognition individually

Single- and multi-microphone speech dereverberation using spectral enhancement

In speech communication systems, such as voice-controlled systems, hands-free mobile telephones, and hearing aids, the received microphone signals are degraded by room reverberation, background noise, and other interferences. This signal degradation may lead to total unintelligibility of the speech and decreases the performance of automatic speech recognition systems. In the context of this work reverberation is the process of multi-path propagation of an acoustic sound from its source to one or more microphones. The received microphone signal generally consists of a direct sound, reflections that arrive shortly after the direct sound (commonly called early reverberation), and reflections that arrive after the early reverberation (commonly called late reverberation). Reverberant speech can be described as sounding distant with noticeable echo and colouration. These detrimental perceptual effects are primarily caused by late reverberation, and generally increase with increasing distance between the source and microphone. Conversely, early reverberations tend to improve the intelligibility of speech. In combination with the direct sound it is sometimes referred to as the early speech component. Reduction of the detrimental effects of reflections is evidently of considerable practical importance, and is the focus of this dissertation. More specifically the dissertation deals with dereverberation techniques, i.e., signal processing techniques to reduce the detrimental effects of reflections. In the dissertation, novel single- and multimicrophone speech dereverberation algorithms are developed that aim at the suppression of late reverberation, i.e., at estimation of the early speech component. This is done via so-called spectral enhancement techniques that require a specific measure of the late reverberant signal. This measure, called spectral variance, can be estimated directly from the received (possibly noisy) reverberant signal(s) using a statistical reverberation model and a limited amount of a priori knowledge about the acoustic channel(s) between the source and the microphone(s). In our work an existing single-channel statistical reverberation model serves as a starting point. The model is characterized by one parameter that depends on the acoustic characteristics of the environment. We show that the spectral variance estimator that is based on this model, can only be used when the source-microphone distance is larger than the so-called critical distance. This is, crudely speaking, the distance where the direct sound power is equal to the total reflective power. A generalization of the statistical reverberation model in which the direct sound is incorporated is developed. This model requires one additional parameter that is related to the ratio between the direct sound energy and the sound energy of all reflections. The generalized model is used to derive a novel spectral variance estimator. When the novel estimator is used for dereverberation rather than the existing estimator, and the source-microphone distance is smaller than the critical distance, the dereverberation performance is significantly increased. Single-microphone systems only exploit the temporal and spectral diversity of the received signal. Reverberation, of course, also induces spatial diversity. To additionally exploit this diversity, multiple microphones must be used, and their outputs must be combined by a suitable spatial processor such as the so-called delay and sum beamformer. It is not a priori evident whether spectral enhancement is best done before or after the spatial processor. For this reason we investigate both possibilities, as well as a merge of the spatial processor and the spectral enhancement technique. An advantage of the latter option is that the spectral variance estimator can be further improved. Our experiments show that the use of multiple microphones affords a significant improvement of the perceptual speech quality. The applicability of the theory developed in this dissertation is demonstrated using a hands-free communication system. Since hands-free systems are often used in a noisy and reverberant environment, the received microphone signal does not only contain the desired signal but also interferences such as room reverberation that is caused by the desired source, background noise, and a far-end echo signal that results from a sound that is produced by the loudspeaker. Usually an acoustic echo canceller is used to cancel the far-end echo. Additionally a post-processor is used to suppress background noise and residual echo, i.e., echo which could not be cancelled by the echo canceller. In this work a novel structure and post-processor for an acoustic echo canceller are developed. The post-processor suppresses late reverberation caused by the desired source, residual echo, and background noise. The late reverberation and late residual echo are estimated using the generalized statistical reverberation model. Experimental results convincingly demonstrate the benefits of the proposed system for suppressing late reverberation, residual echo and background noise. The proposed structure and post-processor have a low computational complexity, a highly modular structure, can be seamlessly integrated into existing hands-free communication systems, and affords a significant increase of the listening comfort and speech intelligibility

The influence of channel and source degradations on intelligibility and physiological measurements of effort

Despite the fact that everyday listening is compromised by acoustic degradations, individuals show a remarkable ability to understand degraded speech. However, recent trends in speech perception research emphasise the cognitive load imposed by degraded speech on both normal-hearing and hearing-impaired listeners. The perception of degraded speech is often studied through channel degradations such as background noise. However, source degradations determined by talkers’ acoustic-phonetic characteristics have been studied to a lesser extent, especially in the context of listening effort models. Similarly, little attention has been given to speaking effort, i.e., effort experienced by talkers when producing speech under channel degradations. This thesis aims to provide a holistic understanding of communication effort, i.e., taking into account both listener and talker factors. Three pupillometry studies are presented. In the first study, speech was recorded for 16 Southern British English speakers and presented to normal-hearing listeners in quiet and in combination with three degradations: noise-vocoding, masking and time-compression. Results showed that acoustic-phonetic talker characteristics predicted intelligibility of degraded speech, but not listening effort, as likely indexed by pupil dilation. In the second study, older hearing-impaired listeners were presented fast time-compressed speech under simulated room acoustics. Intelligibility was kept at high levels. Results showed that both fast speech and reverberant speech were associated with higher listening effort, as suggested by pupillometry. Discrepancies between pupillometry and perceived effort ratings suggest that both methods should be employed in speech perception research to pinpoint processing effort. While findings from the first two studies support models of degraded speech perception, emphasising the relevance of source degradations, they also have methodological implications for pupillometry paradigms. In the third study, pupillometry was combined with a speech production task, aiming to establish an equivalent to listening effort for talkers: speaking effort. Normal-hearing participants were asked to read and produce speech in quiet or in the presence of different types of masking: stationary and modulated speech-shaped noise, and competing-talker masking. Results indicated that while talkers acoustically enhance their speech more under stationary masking, larger pupil dilation associated with competing-speaker masking reflected higher speaking effort. Results from all three studies are discussed in conjunction with models of degraded speech perception and production. Listening effort models are revisited to incorporate pupillometry results from speech production paradigms. Given the new approach of investigating source factors using pupillometry, methodological issues are discussed as well. The main insight provided by this thesis, i.e., the feasibility of applying pupillometry to situations involving listener and talker factors, is suggested to guide future research employing naturalistic conversations

Blind identification of acoustic systems and enhancement of reverberant speech

Imperial Users onl