Coding Strategies for Cochlear Implants Under Adverse Environments

Cochlear implants are electronic prosthetic devices that restores partial hearing in patients with severe to profound hearing loss. Although most coding strategies have significantly improved the perception of speech in quite listening conditions, there remains limitations on speech perception under adverse environments such as in background noise, reverberation and band-limited channels, and we propose strategies that improve the intelligibility of speech transmitted over the telephone networks, reverberated speech and speech in the presence of background noise. For telephone processed speech, we propose to examine the effects of adding low-frequency and high- frequency information to the band-limited telephone speech. Four listening conditions were designed to simulate the receiving frequency characteristics of telephone handsets. Results indicated improvement in cochlear implant and bimodal listening when telephone speech was augmented with high frequency information and therefore this study provides support for design of algorithms to extend the bandwidth towards higher frequencies. The results also indicated added benefit from hearing aids for bimodal listeners in all four types of listening conditions. Speech understanding in acoustically reverberant environments is always a difficult task for hearing impaired listeners. Reverberated sounds consists of direct sound, early reflections and late reflections. Late reflections are known to be detrimental to speech intelligibility. In this study, we propose a reverberation suppression strategy based on spectral subtraction to suppress the reverberant energies from late reflections. Results from listening tests for two reverberant conditions (RT60 = 0.3s and 1.0s) indicated significant improvement when stimuli was processed with SS strategy. The proposed strategy operates with little to no prior information on the signal and the room characteristics and therefore, can potentially be implemented in real-time CI speech processors. For speech in background noise, we propose a mechanism underlying the contribution of harmonics to the benefit of electroacoustic stimulations in cochlear implants. The proposed strategy is based on harmonic modeling and uses synthesis driven approach to synthesize the harmonics in voiced segments of speech. Based on objective measures, results indicated improvement in speech quality. This study warrants further work into development of algorithms to regenerate harmonics of voiced segments in the presence of noise

Electroacoustic and Behavioural Evaluation of Hearing Aid Digital Signal Processing Features

Modern digital hearing aids provide an array of features to improve the user listening experience. As the features become more advanced and interdependent, it becomes increasingly necessary to develop accurate and cost-effective methods to evaluate their performance. Subjective experiments are an accurate method to determine hearing aid performance but they come with a high monetary and time cost. Four studies that develop and evaluate electroacoustic hearing aid feature evaluation techniques are presented. The first study applies a recent speech quality metric to two bilateral wireless hearing aids with various features enabled in a variety of environmental conditions. The study shows that accurate speech quality predictions are made with a reduced version of the original metric, and that a portion of the original metric does not perform well when applied to a novel subjective speech quality rating database. The second study presents a reference free (non-intrusive) electroacoustic speech quality metric developed specifically for hearing aid applications and compares its performance to a recent intrusive metric. The non-intrusive metric offers the advantage of eliminating the need for a shaped reference signal and can be used in real time applications but requires a sacrifice in prediction accuracy. The third study investigates the digital noise reduction performance of seven recent hearing aid models. An electroacoustic measurement system is presented that allows the noise and speech signals to be separated from hearing aid recordings. It is shown how this can be used to investigate digital noise reduction performance through the application of speech quality and speech intelligibility measures. It is also shown how the system can be used to quantify digital noise reduction attack times. The fourth study presents a turntable-based system to investigate hearing aid directionality performance. Two methods to extract the signal of interest are described. Polar plots are presented for a number of hearing aid models from recordings generated in both the free-field and from a head-and-torso simulator. It is expected that the proposed electroacoustic techniques will assist Audiologists and hearing researchers in choosing, benchmarking, and fine-tuning hearing aid features

OBJECTIVE AND SUBJECTIVE EVALUATION OF DEREVERBERATION ALGORITHMS

Reverberation significantly impacts the quality and intelligibility of speech. Several dereverberation algorithms have been proposed in the literature to combat this problem. A majority of these algorithms utilize a single channel and are developed for monaural applications, and as such do not preserve the cues necessary for sound localization. This thesis describes a blind two-channel dereverberation technique that improves the quality of speech corrupted by reverberation while preserving cues that affect localization. The method is based by combining a short term (2ms) and long term (20ms) weighting function of the linear prediction (LP) residual of the input signal. The developed and other dereverberation algorithms are evaluated objectively and subjectively in terms of sound quality and localization accuracy. The binaural adaptation provides a significant increase in sound quality while removing the loss in localization ability found in the bilateral implementation

Near end listening enhancement in realistic environments

Speech playback is harder to understand in noise. Near End Listening Enhancement algorithms try to overcomethe problem by enhancing the speech signal before it is played by a device. Different strategies have beentried, achieving variable degrees of success in specific noise conditions. Such technologies, however, are oftentested in artificial settings - with controlled noise sources and no reverberation. The purpose of this study isto compare a set of state-of-the-art algorithms based on different approaches (adaptive vs non-adaptive, withor without a compensation for reverberation) in simulated real- life scenarios. Binaural noise recordings andimpulse responses of real environments have been used to create two representative scenarios in which speechplayback may occur, namely a domestic and a public space. A preliminary study with N=24 subjects revealedthe need for higher SNRs in the realistic settings (in comparison to controlled noise conditions) in order to obtainthe same levels of intelligibility for plain speech. The goal of the main study is to assess the impact of noiseadaptivity and reverberation awareness in realistic scenarios, in order to better understand how to make speechplayback more robust to noise in real-life situations

Speech intelligibility prediction in reverberation: Towards an integrated model of speech transmission, spatial unmasking, and binaural de-reverberation

Room acoustic indicators of intelligibility have focused on the effects of temporal smearing of speech by reverberation and masking by diffuse ambient noise. In the presence of a discrete noise source, these indicators neglect the binaural listener's ability to separate target speech from noise. Lavandier and Culling [(2010). J. Acoust. Soc. Am. 127, 387–399] proposed a model that incorporates this ability but neglects the temporal smearing of speech, so that predictions hold for near-field targets. An extended model based on useful-to-detrimental (U/D) ratios is presented here that accounts for temporal smearing, spatial unmasking, and binaural de-reverberation in reverberant environments. The influence of the model parameters was tested by comparing the model predictions with speech reception thresholds measured in three experiments from the literature. Accurate predictions were obtained by adjusting the parameters to each room. Room-independent parameters did not lead to similar performances, suggesting that a single U/D model cannot be generalized to any room. Despite this limitation, the model framework allows to propose a unified interpretation of spatial unmasking, temporal smearing, and binaural de-reverberation. I. INTROD