Objective Measure Of Speech Intelligibility Research Articles

Neural envelope tracking predicts speech intelligibility and hearing aid benefit in children with hearing loss

Early assessment of hearing aid benefit is crucial, as the extent to which hearing aids provide audible speech information predicts speech and language outcomes. A growing body of research has proposed neural envelope tracking as an objective measure of speech intelligibility, particularly for individuals unable to provide reliable behavioral feedback. However, its potential for evaluating speech intelligibility and hearing aid benefit in children with hearing loss remains unexplored. In this study, we investigated neural envelope tracking in children with permanent hearing loss through two separate experiments. EEG data were recorded while children listened to age-appropriate stories (Experiment 1) or an animated movie (Experiment 2) under aided and unaided conditions (using personal hearing aids) at multiple stimulus intensities. Neural envelope tracking was evaluated using a linear decoder reconstructing the speech envelope from the EEG in the delta band (0.5-4 Hz). Additionally, we calculated temporal response functions (TRFs) to investigate the spatio-temporal dynamics of the response. In both experiments, neural tracking increased with increasing stimulus intensity, but only in the unaided condition. In the aided condition, neural tracking remained stable across a wide range of intensities, as long as speech intelligibility was maintained. Similarly, TRF amplitudes increased with increasing stimulus intensity in the unaided condition, while in the aided condition significant differences were found in TRF latency rather than TRF amplitude. This suggests that decreasing stimulus intensity does not necessarily impact neural tracking. Furthermore, the use of personal hearing aids significantly enhanced neural envelope tracking, particularly in challenging speech conditions that would be inaudible when unaided. Finally, we found a strong correlation between neural envelope tracking and behaviorally measured speech intelligibility for both narrated stories (Experiment 1) and movie stimuli (Experiment 2). Altogether, these findings indicate that neural envelope tracking could be a valuable tool for predicting speech intelligibility benefits derived from personal hearing aids in hearing-impaired children. Incorporating narrated stories or engaging movies expands the accessibility of these methods even in clinical settings, offering new avenues for using objective speech measures to guide pediatric audiology decision-making.

Results of the second “clarity” enhancement challenge for hearing devices

The clarity enhancement challenges (CECs) seek to facilitate development of novel processing techniques for improving the intelligibility of speech in noise for hearing-aid users through a series of signal-processing challenges. Each challenge provides entrants with a set of stimuli for development and testing of their algorithms. The performance of the algorithms is assessed using objective measures of speech intelligibility and subjective measures conducted with a panel of hearing-impaired listeners. CEC2 featured more complex listening environments than CEC1 with multiple interfering sound sources (speech, music, household appliance sounds) within a simulated living-room environment at signal-to-noise ratios (SNRs) from −12 to + 4 dB. In addition, head rotation towards the target speech was introduced. Target speech came from a new dataset of 10,000 different English sentences spoken by 40 actors speaking 250 sentences each (Graetzer S et al., 2022 Data in Brief 41, 107961). The objective assessment was provided by HASPI (Kates & Arehart, 2021 Speech Comm 131, 35–46). All 18 entries achieved substantial improvements in HASPI, averaging 0.55 across all systems and SNRs. Improvements were greatest (averaging 0.61) for SNRs between −8 and 0 dB. The best-performing system achieved HASPI scores above 0.9 for all SNRs. Listening-test data will be reported.

Comparison of Speech Quality and Intelligibility Assessments in University Classrooms

Estimates of speech quality and intelligibility for three university classrooms of small, medium and large sizes are presented. The quality and intelligibility of speech were assessed by objective methods using binaural room impulse responses, measured at 5-6 points of the premises. The measures of speech quality were log-spectral distortion (LSD), bark spectral distortion (BSD) and perceptual evaluation of speech quality (PESQ), and the objective measure of speech intelligibility was the speech transmission index (STI). Among the quality measures considered, only BSD is shown to be highly correlated with STI measures for all three classrooms. In this case, correlation coefficient R varies from minus 0.6 for a small room to minus 0.98 for a large room. The close relationship between PESQ and STI is observed only in the case of a large classroom (R = 0.96-0.99), and the LSD measure was found to be uncorrelated with STI for premises of all sizes. The obtained results can serve as a justification for the use of BSD instead of STI, and vice versa, in the acoustic examination of classrooms of different sizes.

Utility of the Intelligibility in Context Scale for Predicting Speech Intelligibility of Children with Cerebral Palsy.

The Intelligibility in Context Scale (ICS) is a widely used, efficient tool for describing a child’s speech intelligibility. Few studies have explored the relationship between ICS scores and transcription intelligibility scores, which are the gold standard for clinical measurement. This study examined how well ICS composite scores predicted transcription intelligibility scores among children with cerebral palsy (CP), how well individual questions from the ICS differentially predicted transcription intelligibility scores, and how well the ICS composite scores differentiated between children with and without speech motor impairment. Parents of 48 children with CP, who were approximately 13 years of age, completed the ICS. Ninety-six adult naïve listeners provided orthographic transcriptions of children’s speech. Transcription intelligibility scores were regressed on ICS composite scores and individual item scores. Dysarthria status was regressed on ICS composite scores. Results indicated that ICS composite scores were moderately strong predictors of transcription intelligibility scores. One individual ICS item differentially predicted transcription intelligibility scores, and dysarthria severity influenced how well ICS composite scores differentiated between children with and without speech motor impairment. Findings suggest that the ICS has potential clinical utility for children with CP, especially when used with other objective measures of speech intelligibility.

Predicting speech intelligibility from EEG in a non-linear classification paradigm * *Submitted for review on 7 June 2021. The research conducted in this paper is funded by KU Leuven Special Research Fund C24/18/099 (C2 project to Tom Francart and Hugo Van hamme), by a PhD Grant (1S89620N) of the Research Foundation Flanders (FWO) and from the European Research Council (ERC)

Objective. Currently, only behavioral speech understanding tests are available, which require active participation of the person being tested. As this is infeasible for certain populations, an objective measure of speech intelligibility is required. Recently, brain imaging data has been used to establish a relationship between stimulus and brain response. Linear models have been successfully linked to speech intelligibility but require per-subject training. We present a deep-learning-based model incorporating dilated convolutions that operates in a match/mismatch paradigm. The accuracy of the model’s match/mismatch predictions can be used as a proxy for speech intelligibility without subject-specific (re)training. Approach. We evaluated the performance of the model as a function of input segment length, electroencephalography (EEG) frequency band and receptive field size while comparing it to multiple baseline models. Next, we evaluated performance on held-out data and finetuning. Finally, we established a link between the accuracy of our model and the state-of-the-art behavioral MATRIX test. Main results. The dilated convolutional model significantly outperformed the baseline models for every input segment length, for all EEG frequency bands except the delta and theta band, and receptive field sizes between 250 and 500 ms. Additionally, finetuning significantly increased the accuracy on a held-out dataset. Finally, a significant correlation (r = 0.59, p = 0.0154) was found between the speech reception threshold (SRT) estimated using the behavioral MATRIX test and our objective method. Significance. Our method is the first to predict the SRT from EEG for unseen subjects, contributing to objective measures of speech intelligibility.

Assessment of speech intelligibility in university lecture rooms of different sizes using objective and subjective methods

The scores of speech intelligibility, obtained using objective and subjective methods for three university lecture rooms of the small, medium, and large sizes with different degrees of filling, were presented. The problem of achieving high speech intelligibility is relevant for both students and university administration, and for architects designing or reconstructing lecture rooms. Speech intelligibility was assessed using binaural room impulse responses which applied an artificial head and non-professional quality audio equipment for measuring. The Speech Transmission Index was an objective measure of speech intelligibility, while the subjective evaluation of speech intelligibility was carried out using the articulation method. Comparative analysis of the effectiveness of parameters of impulse response as a measure of speech intelligibility showed that Early Decay Time exceeded the score of the T30 reverberation time but was ineffective in a small lecture room. The C50 clarity index for all the considered lecture rooms was the most informative. Several patterns determined by the influence of early sound reflections on speech intelligibility were detected. Specifically, it was shown that an increase in the ratio of the energy of early reflections to the energy of direct sound leads to a decrease in speech intelligibility. The exceptions are small, up to 30‒40 cm, distances from the back wall of the room, where speech intelligibility is usually slightly higher than in the middle of the room. At a distance of 0.7–1.7 m from the side walls of the room, speech intelligibility is usually worse for the ear, which is closer to the wall. The usefulness of the obtained results lies in refining the quantitative characteristics of the influence of early reflections of sound on speech intelligibility at different points of lecture rooms.

The effect of stimulus intensity on neural envelope tracking

Objectives In recent years, there has been significant interest in recovering the temporal envelope of a speech signal from the neural response to investigate neural speech processing. The research focus is now broadening from neural speech processing in normal-hearing listeners towards hearing-impaired listeners. When testing hearing-impaired listeners, speech has to be amplified to resemble the effect of a hearing aid and compensate for peripheral hearing loss. Today it is not known with certainty how or if neural speech tracking is influenced by sound amplification. As these higher intensities could influence the outcome, we investigated the influence of stimulus intensity on neural speech tracking. Design We recorded the electroencephalogram (EEG) of 20 normal-hearing participants while they listened to a narrated story. The story was presented at intensities from 10 to 80 dB A. To investigate the brain responses, we analyzed neural tracking of the speech envelope by reconstructing the envelope from the EEG using a linear decoder and by correlating the reconstructed with the actual envelope. We investigated the delta (0.5–4 Hz) and the theta (4–8 Hz) band for each intensity. We also investigated the latencies and amplitudes of the responses in more detail using temporal response functions, which are the estimated linear response functions between the stimulus envelope and the EEG. Results Neural envelope tracking is dependent on stimulus intensity in both the TRF and envelope reconstruction analysis. However, provided that the decoder is applied to the same stimulus intensity as it was trained on, envelope reconstruction is robust to stimulus intensity. Besides, neural envelope tracking in the delta (but not theta) band seems to relate to speech intelligibility. Similar to the linear decoder analysis, TRF amplitudes and latencies are dependent on stimulus intensity: The amplitude of peak 1 (30-50 ms) increases, and the latency of peak 2 (140–160 ms) decreases with increasing stimulus intensity. Conclusion Although brain responses are influenced by stimulus intensity, neural envelope tracking is robust to stimulus intensity when using the same intensity to test and train the decoder. Therefore we can assume that intensity will not be a confounder when testing hearing-impaired participants with amplified speech using the linear decoder approach. In addition, neural envelope tracking in the delta band appears to be correlated with speech intelligibility, showing the potential of neural envelope tracking as an objective measure of speech intelligibility.

The Effect of Stimulus Choice on an EEG-Based Objective Measure of Speech Intelligibility.

Recently, an objective measure of speech intelligibility (SI), based on brain responses derived from the electroencephalogram (EEG), has been developed using isolated Matrix sentences as a stimulus. We investigated whether this objective measure of SI can also be used with natural speech as a stimulus, as this would be beneficial for clinical applications. We recorded the EEG in 19 normal-hearing participants while they listened to two types of stimuli: Matrix sentences and a natural story. Each stimulus was presented at different levels of SI by adding speech weighted noise. SI was assessed in two ways for both stimuli: (1) behaviorally and (2) objectively by reconstructing the speech envelope from the EEG using a linear decoder and correlating it with the acoustic envelope. We also calculated temporal response functions (TRFs) to investigate the temporal characteristics of the brain responses in the EEG channels covering different brain areas. For both stimulus types, the correlation between the speech envelope and the reconstructed envelope increased with increasing SI. In addition, correlations were higher for the natural story than for the Matrix sentences. Similar to the linear decoder analysis, TRF amplitudes increased with increasing SI for both stimuli. Remarkable is that although SI remained unchanged under the no-noise and +2.5 dB SNR conditions, neural speech processing was affected by the addition of this small amount of noise: TRF amplitudes across the entire scalp decreased between 0 and 150 ms, while amplitudes between 150 and 200 ms increased in the presence of noise. TRF latency changes in function of SI appeared to be stimulus specific: the latency of the prominent negative peak in the early responses (50 to 300 ms) increased with increasing SI for the Matrix sentences, but remained unchanged for the natural story. These results show (1) the feasibility of natural speech as a stimulus for the objective measure of SI; (2) that neural tracking of speech is enhanced using a natural story compared to Matrix sentences; and (3) that noise and the stimulus type can change the temporal characteristics of the brain responses. These results might reflect the integration of incoming acoustic features and top-down information, suggesting that the choice of the stimulus has to be considered based on the intended purpose of the measurement.

Predicting the impact of hearing aid processing on speech intelligibility

Speech intelligibility is usually assessed using subjective tests, but several objective measures of speech intelligibility have also been proposed. This study compares intelligibility of IEEE sentences in collocated speech-shaped noise, recorded through a low-cost amplifier and three current-issue NHS hearing aids with single-channel noise reduction settings switched on and off. Results from twenty-one normal hearing listeners indicates that single-channel noise reduction algorithms can significantly improve intelligibility of noisy speech (p < 0.05), but no differences can be seen between different hearing aid models currently available on the NHS. The low-cost, off-the shelf hearing amplifier performed significantly worse than the NHS prescribed devices. Three objective speech intelligibility measures were applied to the recordings. None of the objective metrics was found to accurately predict the outcomes seen in this study for all hearing aid conditions, though general trends can be predicted (r = 0.83 overall, but for any discrete signal-to-noise ratio across all conditions, maximum r = 0.64). Machine-learning approaches were used to refit parameters from the best performing of these metrics. Although performance was improved, problems in predicting particular conditions remain, suggesting that objective measures do not encompass all relevant factors. [Action on Hearing Loss (England/Wales Registered Charity Number 207720).]Speech intelligibility is usually assessed using subjective tests, but several objective measures of speech intelligibility have also been proposed. This study compares intelligibility of IEEE sentences in collocated speech-shaped noise, recorded through a low-cost amplifier and three current-issue NHS hearing aids with single-channel noise reduction settings switched on and off. Results from twenty-one normal hearing listeners indicates that single-channel noise reduction algorithms can significantly improve intelligibility of noisy speech (p < 0.05), but no differences can be seen between different hearing aid models currently available on the NHS. The low-cost, off-the shelf hearing amplifier performed significantly worse than the NHS prescribed devices. Three objective speech intelligibility measures were applied to the recordings. None of the objective metrics was found to accurately predict the outcomes seen in this study for all hearing aid conditions, though general trends can be predicted (r = 0....

A Physiologically Inspired Model for Solving the Cocktail Party Problem

At a cocktail party, we can broadly monitor the entire acoustic scene to detect important cues (e.g., our names being called, or the fire alarm going off), or selectively listen to a target sound source (e.g., a conversation partner). It has recently been observed that individual neurons in the avian field L (analog to the mammalian auditory cortex) can display broad spatial tuning to single targets and selective tuning to a target embedded in spatially distributed sound mixtures. Here, we describe a model inspired by these experimental observations and apply it to process mixtures of human speech sentences. This processing is realized in the neural spiking domain. It converts binaural acoustic inputs into cortical spike trains using a multi-stage model composed of a cochlear filter-bank, a midbrain spatial-localization network, and a cortical network. The output spike trains of the cortical network are then converted back into an acoustic waveform, using a stimulus reconstruction technique. The intelligibility of the reconstructed output is quantified using an objective measure of speech intelligibility. We apply the algorithm to single and multi-talker speech to demonstrate that the physiologically inspired algorithm is able to achieve intelligible reconstruction of an “attended” target sentence embedded in two other non-attended masker sentences. The algorithm is also robust to masker level and displays performance trends comparable to humans. The ideas from this work may help improve the performance of hearing assistive devices (e.g., hearing aids and cochlear implants), speech-recognition technology, and computational algorithms for processing natural scenes cluttered with spatially distributed acoustic objects.

A new perceptually weighted cost function in deep neural network based speech enhancement systems

Speech intelligibility improvement is an important task to increase human perception in telecommunication systems and hearing aids when the speech is degraded by the background noises. Although, deep neural network (DNN) based learning architectures which use mean square error (MSE) as the cost function has been found to be very successful in speech enhancement areas, they typically attempt to enhance the speech quality by uniformly optimizing the separation of a target speech signal from a noisy observation over all frequency bands. In this work, we propose a new cost function which further focuses on speech intelligibility improvement based on a psychoacoustic model. The band-importance function, which is a principal component of speech intelligibility index (SII), has been used to determine the relative contribution to speech intelligibility provided by each frequency band in learning algorithm. In addition, we augment a signal to noise ratio (SNR) estimation to the network to improve the generalization of the method to unseen noisy conditions. The performance of the proposed MSE cost function is compared with the conventional MSE cost function in the same conditions. Our approach shows better performance in objective speech intelligibility measures such as coherence SII (CSII) and short-time objective intelligibility (STOI), while mitigating quality scores in perceptual evaluation of speech quality (PESQ) and speech distortion (SD) measure.

On the feasibility of using a bispectral measure as a nonintrusive predictor of speech intelligibility

The presence of background noise or nonlinear distortions encountered in real-world situations often reduces the intelligibility of speech signals. Several objective measurements and prediction procedures have been developed to assess speech intelligibility in noise. Most of the existing measures are, however, suitable for only a subset of specified forms of distortion. This study developed a reliable, reference-free speech intelligibility metric that uses the properties of an acoustic signal to predict the effects of a wide range of distortions that influence speech intelligibility in quiet and noisy conditions. The bispectral speech intelligibility metric (BSIM), was developed by extracting the features from the spectrogram of speech signals using the third-order statistics, which are collectively known as the bispectrum. Speech intelligibility scores predicted by the BSIM were compared to behavioral speech intelligibility scores in quiet and noise. The performance of the BSIM was also compared with that of several widely used speech intelligibility metrics. Results showed that the BSIM can successfully predict nonlinear distortions, such as peak-clipping and center-clipping, as well as time domain distortions, such as phase-jitter and reverberation. Unlike existing metrics, such as the articulation index and speech transmission index, the BSIM successfully captured the effect of fluctuating noise on speech intelligibility and predicted the effects of the degradation of noisy speech processed by the ideal time-frequency segregation method. The BSIM presents a reliable, reference-free, and objective measure of speech intelligibility that can provide real-time predictions of the effect of signal processing and acoustics distortion on speech intelligibility in quiet and noise. In addition, the BSIM could be used to analyze algorithms that process noisy speech.

Cortical correlates of speech intelligibility measured using functional near-infrared spectroscopy (fNIRS)

Functional neuroimaging has identified that the temporal, frontal and parietal cortex support core aspects of speech processing. An objective measure of speech intelligibility based on cortical activation in these brain regions would be extremely useful to speech communication and hearing device applications. In the current study, we used noise-vocoded speech to examine cortical correlates of speech intelligibility in normally-hearing listeners using functional near-infrared spectroscopy (fNIRS), a non-invasive, neuroimaging technique that is fully-compatible with hearing devices, including cochlear implants. In twenty-three normally-hearing adults we measured (1) activation in superior temporal, inferior frontal and inferior parietal cortex bilaterally and (2) behavioural speech intelligibility. Listeners heard noise-vocoded sentences targeting five equally spaced levels of intelligibility between 0 and 100% correct. Activation in superior temporal regions increased linearly with intelligibility. This relationship appears to have been driven in part by changing acoustic properties across stimulation conditions, rather than solely by intelligibility per se. Superior temporal activation was also predictive of individual differences in intelligibility in a challenging listening condition. Beyond superior temporal cortex, we identified regions in which activation varied non-linearly with intelligibility. For example, in left inferior frontal cortex, activation peaked in response to heavily degraded, yet still somewhat intelligible, speech. Activation in this region was linearly related to response time on a simultaneous behavioural task, suggesting it may contribute to decision making. Our results indicate that fNIRS has the potential to provide an objective measure of speech intelligibility in normally-hearing listeners. Should these results be found to apply similarly in the case of individuals listening through a cochlear implant, fNIRS would demonstrate potential for a clinically useful measure not only of speech intelligibility, but also of listening effort.

Non-intrusive codebook-based intelligibility prediction

In recent years, there has been an increasing interest in objective measures of speech intelligibility in the speech processing community. Important progress has been made in intrusive measures of intelligibility, where the Short-Time Objective Intelligibility (STOI) method has become the de facto standard. Online adaptation of signal processing in, for example, hearing aids, in accordance with the listening conditions, requires a non-intrusive measure of intelligibility. Presently, however, no good non-intrusive measures exist for noisy, nonstationary conditions. In this paper, we propose a novel, non-intrusive method for intelligiblity prediction in noisy conditions. The proposed method is based on STOI, which measures long-term correlations in the clean and degraded speech. Here, we propose to estimate the clean speech using a codebook-based approach that jointly models the speech and noisy spectra, parametrized by auto-regressive parameters, using pre-trained codebooks of both speech and noise. In experiments, the proposed method is demonstrated to be capable of accurately predicting the intelligibility scores obtained with STOI from oracle information. Moreover, the results are validated in listening tests that confirm that the proposed method can estimate intelligibility from noisy speech over a range of signal-to-noise ratios.

Speech intelligibility after repair of cleft lip and palate.

Background: Intelligibility refers to understandability of speech; and lack of it can negatively affect children’s overall communication effectiveness. Children with repaired cleft lip and/or cleft palate (CL/P) may experience poor speech intelligibility. This study aimed at evaluating speech intelligibility in children with repaired CL/P who had not been referred to speech-language pathology clinics for early intervention. Methods: Sixty-four monolingual Persian-speaking children, 32 children with repaired CL/P, and 32 controls aged 3 to 5 years participated in this survey. Their speech intelligibility was evaluated through the Persian Speech Intelligibility Test and was normalized on children 3 to 5 years. Each speech sample was heard by a speech and language pathologist (SLP), as well as 2 nonprofessional listeners. Two objective measures of speech intelligibility including Percentage of Consonants Correct (PCC) and Percentage of Intelligible Words (PIW) were used in this research. Results: Children with CL/P were significantly outperformed by their peers in PCC (p= 0.0001) and PIW (p= 0.0001). More than half of the case group had compensatory errors and 40.6% had obligatory errors. The PCC and the PIW were statistically different in children with different rates of hyper nasality (p= 0.001). Conclusion: Speech intelligibility of children with CL/P is impaired due to their articulation disorders (obligatory and compensatory errors). This survey documents the necessity for speech therapy for increasing speech intelligibility in this population.

Predicting the Intelligibility of Noisy and Nonlinearly Processed Binaural Speech

Objective speech intelligibility measures are gaining popularity in the development of speech enhancement algorithms and speech processing devices such as hearing aids. Such devices may process the input signals nonlinearly and modify the binaural cues presented to the user. We propose a method for predicting the intelligibility of noisy and nonlinearly processed binaural speech. This prediction is based on the noisy and processed signal as well as a clean speech reference signal. The method is obtained by extending a modified version of the short-time objective intelligibility STOI measure with a modified equalization-cancellation EC stage. We evaluate the performance of the method by comparing the predictions with measured intelligibility from four listening experiments. These comparisons indicate that the proposed measure can provide accurate predictions of 1 the intelligibility of diotic speech with an accuracy similar to that of the original STOI measure, 2 speech reception thresholds SRTs in conditions with a frontal target speaker and a single interferer in the horizontal plane, 3 SRTs in conditions with a frontal target and a single interferer when ideal time frequency segregation ITFS is applied to the left and right ears separately, and 4 the advantage of two-microphone beamforming as applied in state-of-the-art hearing aids. A MATLAB implementation of the proposed measure is available online1.

An evaluation of objective measures for intelligibility prediction of time-frequency weighted noisy speech

Existing objective speech-intelligibility measures are suitable for several types of degradation, however, it turns out that they are less appropriate in cases where noisy speech is processed by a time-frequency weighting. To this end, an extensive evaluation is presented of objective measure for intelligibility prediction of noisy speech processed with a technique called ideal time frequency (TF) segregation. In total 17 measures are evaluated, including four advanced speech-intelligibility measures (CSII, CSTI, NSEC, DAU), the advanced speech-quality measure (PESQ), and several frame-based measures (e.g., SSNR). Furthermore, several additional measures are proposed. The study comprised a total number of 168 different TF-weightings, including unprocessed noisy speech. Out of all measures, the proposed frame-based measure MCC gave the best results (ρ = 0.93). An additional experiment shows that the good performing measures in this study also show high correlation with the intelligibility of single-channel noise reduced speech.

Speech intelligibility improvement in rooms using microphone arrays.

Microphones arrays reduce the effects of reverberation and background noise as compared to a single microphone. The resulting improvement in speech intelligibility in rooms is investigated here, following the approach discussed by Houtgast et al. [Acustica 46, 60–72 (1980)]. Room characteristics (volume, reverberation time), the background noise spectrum, and the source-receiver separation are used to compute a modulation transfer function. This function is input into the procedure described in IEC standard 60268-16(2003) to arrive at an objective measure of speech intelligibility, the speech transmission index (STI). Doing this for both omnidirectional and microphone array receivers, the improvement in intelligibility is determined. The signal source has the spectral shape of a human talker, as given in the IEC standard; the background noise spectrum is based on measurements made in a restaurant. The benefit of using microphone arrays is discussed for various conditions.

Effect of Analysis Window Duration on Speech Intelligibility

In this letter, we investigate the effect of the analysis window duration on speech intelligibility in a systematic way. In speech processing, the short-time magnitude spectrum is believed to contain the majority of the intelligible information. Consequently, in our experiments, we construct speech stimuli based purely on the short-time magnitude spectrum. We conduct subjective listening tests in the form of a consonant recognition task to assess intelligibility as a function of analysis window duration. In our investigations, we also employ three objective speech intelligibility measures based on the speech transmission index (STI). The experimental results show that the analysis window duration of 15-35 ms is the optimum choice when speech is reconstructed from the short-time magnitude spectrum.

Effect of Slow-Acting Wide Dynamic Range Compression on Measures of Intelligibility and Ratings of Speech Quality in Simulated-Loss Listeners

The purpose of this study was twofold: (a) to determine the extent to which 4-channel, slow-acting wide dynamic range amplitude compression (WDRC) can counteract the perceptual effects of reduced auditory dynamic range and (b) to examine the relation between objective measures of speech intelligibility and categorical ratings of speech quality for sentences processed with slow-acting WDRC. Multiband expansion was used to simulate the effects of elevated thresholds and loudness recruitment in normal hearing listeners. While some previous studies have shown that WDRC can improve both speech intelligibility and quality, others have found no benefit. The current experiment shows that moderate amounts of compression can provide a small but significant improvement in speech intelligibility, relative to linear amplification, for simulated-loss listeners with small dynamic ranges (i.e., flat, moderate hearing loss). This benefit was found for speech at conversational levels, both in quiet and in a background of babble. Simulated-loss listeners with large dynamic ranges (i.e., sloping, mild-to-moderate hearing loss) did not show any improvement. Comparison of speech intelligibility scores and subjective ratings of intelligibility showed that listeners with simulated hearing loss could accurately judge the overall intelligibility of speech. However, in all listeners, ratings of pleasantness decreased as the compression ratio increased. These findings suggest that subjective measures of speech quality should be used in conjunction with either objective or subjective measures of speech intelligibility to ensure that participant-selected hearing aid parameters optimize both comfort and intelligibility.