Vijay Parsa

Adaptive stimulus artifact reduction in noncortical somatosensory evoked potential studies

Somatosensory evoked potentials (SEPs) are an important class of bioelectric signals which contain clinically valuable information. The surface measurements of these potentials are often contaminated by a stimulus evoked artifact. The stimulus artifact (SA), depending upon the stimulator and measurement system characteristics, may obscure some of the information carried by the SEPs. Conventional methods for SA reduction employ hardware-based circuits which attempt to eliminate the SA by blanking the input during SA period. However, there is a danger of losing some of the important SEP information, especially if the stimulating and recording electrodes are close together. Here, the authors apply both linear and nonlinear adaptive filtering techniques to the problem of SA reduction. Nonlinear adaptive filters (NAFs) based on truncated second-order Volterra series expansion are discussed and their applicability to SA cancellation is explored through processing both simulated and in vivo SEP data. The performances of the NAF and the finite impulse response (FIR) linear adaptive filter (LAF) are compared by processing experimental SEP data collected from different recording sites. Due to the inherent nonlinearities in the generation of the SA, the NAF is shown to achieve significantly better SA cancellation compared to the LAF.

Multireference adaptive noise cancellation applied to somatosensory evoked potentials

Somatosensory evoked potentials (SEPs) contain information that is useful in diagnosing various physiological disorders. However, surface measurements of these potentials suffer from very poor signal-to-noise ratio (SNR) resulting in imperceptible SEP waveforms. This factor motivates the employment of dedicated signal processing techniques to improve the quality of the waveform. The objective of this research work is to improve the SNR of SEP by eliminating the predominant myoelectric interference. The strategy followed to achieve this goal is to process the SEP signal by multireference adaptive noise cancellation (MRANC). A theoretical model for the MRANC is presented and its performance under the influence of various factors is investigated and compared with other signal processing techniques. The performance of the MRANC is then evaluated by processing simulated and in vivo SEP data. It is found that the MRANC gives a significant improvement in the SNR of the SEP.<<ETX>>

Bayesian model based non-intrusive speech quality evaluation

A novel Bayesian model-based non-intrusive speech quality evaluation (BM-NiSQE) algorithm is presented in this paper. The proposed BM-NiSQE algorithm employs a statistical model approach and Bayesian inference to estimate the speech quality only using the output signal of the system under test. In the proposed algorithm, the speech features are extracted by perceptual spectral analysis. Gaussian mixture density hidden Markov models (GMD-HMMs) are exploited to characterize different speech quality categories, which take into account not only the temporal variations of speech signal but also the spectral statistical characteristics in the perception domain. Based on the trained GMD-HMMs, the prediction of speech quality is carried out by Bayesian inference and minimum mean square error (MMSE) estimation. Preliminary experimental results show that the predicted results of the proposed algorithm correlate well with the subjective quality scores.

Nonlinear Frequency Compression Effects on Sound Quality Ratings of Speech and Music

Frequency lowering technologies offer an alternative amplification solution for severe to profound high frequency hearing losses. While frequency lowering technologies may improve audibility of high frequency sounds, the very nature of this processing can affect the perceived sound quality. This article reports the results from two studies that investigated the impact of a nonlinear frequency compression (NFC) algorithm on perceived sound quality. In the first study, the cutoff frequency and compression ratio parameters of the NFC algorithm were varied, and their effect on the speech quality was measured subjectively with 12 normal hearing adults, 12 normal hearing children, 13 hearing impaired adults, and 9 hearing impaired children. In the second study, 12 normal hearing and 8 hearing impaired adult listeners rated the quality of speech in quiet, speech in noise, and music after processing with a different set of NFC parameters. Results showed that the cutoff frequency parameter had more impact on sound quality ratings than the compression ratio, and that the hearing impaired adults were more tolerant to increased frequency compression than normal hearing adults. No statistically significant differences were found in the sound quality ratings of speech-in-noise and music stimuli processed through various NFC settings by hearing impaired listeners. These findings suggest that there may be an acceptable range of NFC settings for hearing impaired individuals where sound quality is not adversely affected. These results may assist an Audiologist in clinical NFC hearing aid fittings for achieving a balance between high frequency audibility and sound quality.

HMM-based frequency bandwidth extension for speech enhancement using line spectral frequencies

A new hidden Markov model (HMM) based frequency bandwidth extension algorithm using line spectral frequencies (HMM-LSF-FBE) is proposed. The proposed algorithm improves the performance of the traditional LSF-based extension algorithm by exploiting an HMM to indicate the proper representatives of different speech frames, and by applying a minimum mean square criterion to estimate the high-band LSF values. The proposed algorithm has been tested and compared to the traditional LSF-based algorithm in terms of the perceptual evaluation of speech quality (PESQ) objective measure and speech spectrograms. Simulation results show that the proposed algorithm outperforms the traditional method by eliminating undesired whistling sounds completely. In addition, the bandwidth extended speech signals created by the proposed algorithm are significantly more pleasant to the human ear than the original narrowband speech signals from which they are derived.

Objective Quality and Intelligibility Prediction for Users of Assistive Listening Devices: Advantages and limitations of existing tools

This article presents an overview of 12 existing objective speech quality and intelligibility prediction tools. Two classes of algorithms are presented?intrusive and nonintrusive?with the former requiring the use of a reference signal, while the latter does not. Investigated metrics include both those developed for normal hearing (NH) listeners, as well as those tailored particularly for hearing impaired (HI) listeners who are users of assistive listening devices [i.e., hearing aids (HAs) and cochlear implants (CIs)]. Representative examples of those optimized for HI listeners include the speech-to-reverberation modulation energy ratio (SRMR), tailored to HAs (SRMR-HA) and to CIs (SRMR-CI); the modulation spectrum area (ModA); the HA speech quality (HASQI) and perception indices (HASPI); and the perception-model-based quality prediction method for hearing impairments (PEMO-Q-HI). The objective metrics are tested on three subjectively rated speech data sets covering reverberation-alone, noise-alone, and reverberation-plus-noise degradation conditions, as well as degradations resultant from nonlinear frequency compression and different speech enhancement strategies. The advantages and limitations of each measure are highlighted and recommendations are given for suggested uses of the different tools under specific environmental and processing conditions.

Nonintrusive speech quality evaluation using an adaptive neurofuzzy inference system

This letter presents a novel nonintrusive speech quality evaluation method using an adaptive neurofuzzy inference system (ANFIS). The proposed method employed a first-order Sugeno-type fuzzy inference system (FIS) to estimate speech quality using only the output signal of the system under test. This new method was compared with the state-of-the-art nonintrusive quality evaluation standard, the ITU-T P.563 Recommendation, using seven subjective quality databases of the ITU-T P-series Supplementary 23. Experimental results show that the correlation of the proposed method with the subjective quality scores reached 0.8812, with a standard error of 0.3647 across the entire database. This compares favorably with the standard P.563, which provides a correlation and standard error of 0.8422 and 0.4493, respectively.

Active noise reduction audiometry: a prospective analysis of a new approach to noise management in audiometric testing.

Objectives: To develop a new method of screening audiometry that reduces the adverse effects of low frequency background noise by using active noise reduction (ANR) headphone technology.

Evaluation of speech intelligibility and sound localization abilities with hearing aids using binaural wireless technology

Wireless synchronization of the digital signal processing (DSP) features between two hearing aids in a bilateral hearing aid fitting is a fairly new technology. This technology is expected to preserve the differences in time and intensity between the two ears by co-ordinating the bilateral DSP features such as multichannel compression, noise reduction, and adaptive directionality. The purpose of this study was to evaluate the benefits of wireless communication as implemented in two commercially available hearing aids. More specifically, this study measured speech intelligibility and sound localization abilities of normal hearing and hearing impaired listeners using bilateral hearing aids with wireless synchronization of multichannel Wide Dynamic Range Compression (WDRC). Twenty subjects participated; 8 had normal hearing and 12 had bilaterally symmetrical sensorineural hearing loss. Each individual completed the Hearing in Noise Test (HINT) and a sound localization test with two types of stimuli. No specific benefit from wireless WDRC synchronization was observed for the HINT; however, hearing impaired listeners had better localization with the wireless synchronization. Binaural wireless technology in hearing aids may improve localization abilities although the possible effect appears to be small at the initial fitting. With adaptation, the hearing aids with synchronized signal processing may lead to an improvement in localization and speech intelligibility. Further research is required to demonstrate the effect of adaptation to the hearing aids with synchronized signal processing on different aspects of auditory performance.

Interactions between speech coders and disordered speech

We examined the impact of standard speech coders currently used in modern communication systems, on the quality of speech from persons with common speech and voice disorders. Four standardized coders, viz. G. 728 LD-CELP, GSM 6.10 RPE-LTP, FS1016 CELP, FS1015 LPC and the recently proposed US Federal Standard 2400 bps MELP were evaluated with speech samples collected from 30 disordered talkers. Objective speech quality measures, including the auditory distance parameter based on the measuring normalizing blocks technique, and the perceptual speech quality measure, and subjective impressions of speech coder performance were used to assess the interaction between speech coder and speech disorder. Objective speech quality measures revealed that the performance of the LD-CELP and GSM RPE-LTP coders was not measurably influenced by the type of input speech, and that MELP, FS1015 LPC and to a certain extent FS1016 CELP exhibited degraded performance with speech samples from disordered talkers. Results from perceptual experiments were in contrast with the objective measures of speech quality; ratings of speech coder performance indicated that the listeners are less sensitive to coder-induced distortions with abnormal speech samples.