Prior exposure to a reverberant listening environment improves speech intelligibility in adult cochlear implant listeners.

OBJECTIVES: The goal of this study is to investigate whether prior exposure to reverberant listening environment improves speech intelligibility of adult cochlear implant (CI) users. METHODS: Six adult CI users participated in this study. Speech intelligibility was measured in five different simulated reverberant listening environments with two different speech corpuses. Within each listening environment, prior exposure was varied by either having the same environment across all trials (blocked presentation) or having different environment from trial to trial (unblocked). RESULTS: Speech intelligibility decreased as reverberation time increased. Although substantial individual variability was observed, all CI listeners showed an increase in the blocked presentation condition as compared to the unblocked presentation condition for both speech corpuses. CONCLUSION: Prior listening exposure to a reverberant listening environment improves speech intelligibility in adult CI listeners. Further research is required to understand the underlying mechanism of adaptation to listening environment.

Evaluation of the importance of time-frequency contributions to speech intelligibility in noise.

Recent studies on binary masking techniques make the assumption that each time-frequency (T-F) unit contributes an equal amount to the overall intelligibility of speech. The present study demonstrated that the importance of each T-F unit to speech intelligibility varies in accordance with speech content. Specifically, T-F units are categorized into two classes, speech-present T-F units and speech-absent T-F units. Results indicate that the importance of each speech-present T-F unit to speech intelligibility is highly related to the loudness of its target component, while the importance of each speech-absent T-F unit varies according to the loudness of its masker component. Two types of mask errors are also considered, which include miss and false alarm errors. Consistent with previous work, false alarm errors are shown to be more harmful to speech intelligibility than miss errors when the mixture signal-to-noise ratio (SNR) is below 0 dB. However, the relative importance between the two types of error is conditioned on the SNR level of the input speech signal. Based on these observations, a mask-based objective measure, the loudness weighted hit-false, is proposed for predicting speech intelligibility. The proposed objective measure shows significantly higher correlation with intelligibility compared to two existing mask-based objective measures.

Vocoder simulations of highly focused cochlear stimulation with limited dynamic range and discriminable steps.

OBJECTIVES: There is recent interest in focused stimulation of the cochlea via modalities such as tripolar electrical and infrared neural stimulation to improve speech in noise comprehension and music perception. The purpose of this work was to use vocoder-based simulations to investigate speech recognition for broad stimulation (standard monopolar paradigm) versus more focused stimulation under a variety of signal-to-noise ratios, dynamic ranges, and numbers of discriminable loudness steps. DESIGN: Vocoder simulations were used to assess the intelligibility of sentences, consonants, and vowels that were noise vocoded and presented to 7 normal-hearing listeners for identification. A novel aspect of the simulations presented here was the use of nonuniform quantization steps within the dynamic range to more closely simulate the Weber functions observed in cochlear implant users. Intelligibility was assessed for the different filter slopes under a variety of signal-to-noise ratio levels, dynamic ranges, and numbers of discriminable steps. RESULTS: Speech processed via vocoder simulations representing focused stimulation was found to be substantially more intelligible than speech processed via a monopolar electric vocoder simulation, with differences of up to 60 percentage points. There were no significant differences, however, seen between the two focused approaches (signal attenuations of 10 and 17 dB/mm) for the conditions investigated. Speech processed via the highly focused vocoder (17 dB/mm) was robust to constraints on small envelope dynamic range and small number of discriminable steps within the dynamic range, as high performance was maintained with at least a 5 dB dynamic range and eight or more discriminable steps. Significant drops in intelligibility were noted when the number of steps fell below eight. CONCLUSIONS: Highly focused stimulation-tripolar electrical and infrared neural stimulation-has potential for increased performance in noise compared with monopolar stimulation, but much work remains to bear this potential out and to take full advantage of each modality's strengths.

Simultaneous suppression of noise and reverberation in cochlear implants using a ratio masking strategy.

Cochlear implant (CI) recipients' ability to identify words is reduced in noisy or reverberant environments. The speech identification task for CI users becomes even more challenging in conditions where both reverberation and noise co-exist as they mask the spectro-temporal cues of speech in a rather complementary fashion. Ideal channel selection (ICS) was found to result in significantly more intelligible speech when applied to the noisy, reverberant, as well as noisy reverberant speech. In this study, a blind single-channel ratio masking strategy is presented to simultaneously suppress the negative effects of reverberation and noise on speech identification performance for CI users. In this strategy, noise power spectrum is estimated from the non-speech segments of the utterance while reverberation spectral variance is computed as a delayed and scaled version of the reverberant speech spectrum. Based on the estimated noise and reverberation power spectra, a weight between 0 and 1 is assigned to each time-frequency unit to form the final mask. Listening experiments conducted with CI users in two reverberant conditions (T60 = 0.6 and 0.8 s) at a signal-to-noise ratio of 15 dB indicate substantial improvements in speech intelligibility in both reverberant-alone and noisy reverberant conditions considered.

Objective speech intelligibility measurement for cochlear implant users in complex listening environments.

Objective intelligibility measurement allows for reliable, low-cost, and repeatable assessment of innovative speech processing technologies, thus dispensing costly and time-consuming subjective tests. To date, existing objective measures have focused on normal hearing model, and limited use has been found for restorative hearing instruments such as cochlear implants (CIs). In this paper, we have evaluated the performance of five existing objective measures, as well as proposed two refinements to one particular measure to better emulate CI hearing, under complex listening conditions involving noise-only, reverberation-only, and noise-plus-reverberation. Performance is assessed against subjectively rated data. Experimental results show that the proposed CI-inspired objective measures outperformed all existing measures; gains by as much as 22% could be achieved in rank correlation.

Reverberation suppression in cochlear implants using a blind channel-selection strategy.

Reverberation severely degrades speech intelligibility for cochlear implant (CI) users. The ideal reverberant mask (IRM), a binary mask for reverberation suppression which is computed using signal-to-reverberant ratio, was found to yield substantial intelligibility gains for CI users even in highly reverberant environments (e.g., T60 = 1.0 s). Motivated by the intelligibility improvements obtained from IRM, a monaural blind channel-selection criterion for reverberation suppression is proposed. The proposed channel-selection strategy is blind, meaning that prior knowledge of neither the room impulse response nor the anechoic signal is required. By the use of a residual signal obtained from linear prediction analysis of the reverberant signal, the residual-to-reverberant ratio (RRR) of individual frequency channels was employed as the channel-selection criterion. In each frame, the channels with RRR less than an adaptive threshold were retained while the rest were zeroed out. Performance of the proposed strategy was evaluated via intelligibility listening tests conducted with CI users in simulated rooms with two reverberation times of 0.6 and 0.8 s. The results indicate significant intelligibility improvements in both reverberant conditions (over 30 and 40 percentage points in T60 = 0.6 and 0.8 s, respectively). The improvement is comparable to that obtained with the IRM strategy.

Predicting the intelligibility of reverberant speech for cochlear implant listeners with a non-intrusive intelligibility measure.

Reverberation is known to reduce the temporal envelope modulations present in the signal and affect the shape of the modulation spectrum. A non-intrusive intelligibility measure for reverberant speech is proposed motivated by the fact that the area of the modulation spectrum decreases with increasing reverberation. The proposed measure is based on the average modulation area computed across four acoustic frequency bands spanning the signal bandwidth. High correlations (r = 0.98) were observed with sentence intelligibility scores obtained by cochlear implant listeners. Proposed measure outperformed other measures including an intrusive speech-transmission index based measure.

Design and evaluation of a personal digital assistant-based research platform for cochlear implants.

This paper discusses the design, development, features, and clinical evaluation of a personal digital assistant (PDA)-based platform for cochlear implant research. This highly versatile and portable research platform allows researchers to design and perform complex experiments with cochlear implants manufactured by Cochlear Corporation with great ease and flexibility. The research platform includes a portable processor for implementing and evaluating novel speech processing algorithms, a stimulator unit which can be used for electrical stimulation and neurophysiologic studies with animals, and a recording unit for collecting electroencephalogram/evoked potentials from human subjects. The design of the platform for real time and offline stimulation modes is discussed for electric-only and electric plus acoustic stimulation followed by results from an acute study with implant users for speech intelligibility in quiet and noisy conditions. The results are comparable with users' clinical processor and very promising for undertaking chronic studies.

Comparison of two channel selection criteria for noise suppression in cochlear implants.

The performance of current channel selection criteria used in cochlear implant (CI) devices (e.g., maximum selection criterion used in ACE) degrades significantly in the presence of noise. In noisy backgrounds, coding strategies that select the "right" channels for stimulation could potentially produce substantial improvements in intelligibility. In this study, the performance of two alternative channel selection criteria is assessed in terms of intelligibility and subjective quality with CI users in noise. The performance is compared against that of the maximum selection scheme employed in the ACE strategy (comparison is also made with the CIS strategy). Sentences were presented to seven CI users in speech weighted noise (-5, 0, and 5 dB SNR). Both channel selection criteria were implemented under ideal conditions where a priori knowledge of the target and masker was assumed. This was done to assess the full potential benefit of selecting the "right" channels for stimulation in noisy backgrounds. Substantial intelligibility improvement relative to the CI users' daily strategy (i.e., ACE or CIS) was achieved with the two different channel selection criteria under all noisy conditions considered. No significant difference in subjective quality of noisy speech processed by the two channel selection criteria was observed.

Blind binary masking for reverberation suppression in cochlear implants.

A monaural binary time-frequency (T-F) masking technique is proposed for suppressing reverberation. The mask is estimated for each T-F unit by extracting a variance-based feature from the reverberant signal and comparing it against an adaptive threshold. Performance of the estimated binary mask is evaluated in three moderate to relatively high reverberant conditions (T60 = 0.3, 0.6, and 0.8 s) using intelligibility listening tests with cochlear implant users. Results indicate that the proposed T-F masking technique yields significant improvements in intelligibility of reverberant speech even in relatively high reverberant conditions (T60 = 0.8 s). The improvement is hypothesized to result from the recovery of the vowel/consonant boundaries, which are severely smeared in reverberation.

Environment-adaptive speech enhancement for bilateral cochlear implants using a single processor.

A computationally efficient speech enhancement pipeline in noisy environments based on a single-processor implementation is developed for utilization in bilateral cochlear implant systems. A two-channel joint objective function is defined and a closed form solution is obtained based on the weighted-Euclidean distortion measure. The computational efficiency and no need for synchronization aspects of this pipeline make it a suitable solution for real-time deployment. A speech quality measure is used to show its effectiveness in six different noisy environments as compared to a similar one-channel enhancement pipeline when using two separate processors or when using independent sequential processing.

Predicting the speech reception threshold of cochlear implant listeners using an envelope-correlation based measure.

A modulation-based index is proposed for predicting speech intelligibility by cochlear implant (CI) listeners. The input to the proposed index are speech envelopes extracted using the individual CI user's daily strategy, and as such, this approach incorporates information about the number of active electrodes, shape of the compression function and electrical dynamic range. High correlation (r = 0.96) was achieved with the proposed index when evaluated with speech-reception thresholds (SRTs) obtained by CI users in steady and speech-masker conditions. This outcome suggests that the information contained in electrodograms seems to be sufficient for reliably predicting CI user's performance in noise. The proposed index can be used by clinicians to optimize the selection of fitting parameters of individual CI users for better performance in noise.

Contributions of cochlea-scaled entropy and consonant-vowel boundaries to prediction of speech intelligibility in noise.

Recent evidence suggests that spectral change, as measured by cochlea-scaled entropy (CSE), predicts speech intelligibility better than the information carried by vowels or consonants in sentences. Motivated by this finding, the present study investigates whether intelligibility indices implemented to include segments marked with significant spectral change better predict speech intelligibility in noise than measures that include all phonetic segments paying no attention to vowels/consonants or spectral change. The prediction of two intelligibility measures [normalized covariance measure (NCM), coherence-based speech intelligibility index (CSII)] is investigated using three sentence-segmentation methods: relative root-mean-square (RMS) levels, CSE, and traditional phonetic segmentation of obstruents and sonorants. While the CSE method makes no distinction between spectral changes occurring within vowels/consonants, the RMS-level segmentation method places more emphasis on the vowel-consonant boundaries wherein the spectral change is often most prominent, and perhaps most robust, in the presence of noise. Higher correlation with intelligibility scores was obtained when including sentence segments containing a large number of consonant-vowel boundaries than when including segments with highest entropy or segments based on obstruent/sonorant classification. These data suggest that in the context of intelligibility measures the type of spectral change captured by the measure is important.

Real-time automatic tuning of noise suppression algorithms for cochlear implant applications.

The performance of cochlear implants deteriorates in noisy environments compared to quiet conditions. This paper presents an adaptive cochlear implant system, which is capable of classifying the background noise environment in real time for the purpose of adjusting or tuning its noise suppression algorithm to that environment. The tuning is done automatically with no user intervention. Five objective quality measures are used to show the superiority of this adaptive system compared to a conventional fixed noise-suppression system. Steps taken to achieve the real-time implementation of the entire system, incorporating both the cochlear implant speech processing and the background noise suppression, on a portable PDA research platform are presented along with the timing results.

Channel selection in the modulation domain for improved speech intelligibility in noise.

Background noise reduces the depth of the low-frequency envelope modulations known to be important for speech intelligibility. The relative strength of the target and masker envelope modulations can be quantified using a modulation signal-to-noise ratio, (S/N)(mod), measure. Such a measure can be used in noise-suppression algorithms to extract target-relevant modulations from the corrupted (target + masker) envelopes for potential improvement in speech intelligibility. In the present study, envelopes are decomposed in the modulation spectral domain into a number of channels spanning the range of 0-30 Hz. Target-dominant modulations are identified and retained in each channel based on the (S/N)(mod) selection criterion, while modulations which potentially interfere with perception of the target (i.e., those dominated by the masker) are discarded. The impact of modulation-selective processing on the speech-reception threshold for sentences in noise is assessed with normal-hearing listeners. Results indicate that the intelligibility of noise-masked speech can be improved by as much as 13 dB when preserving target-dominant modulations, present up to a modulation frequency of 18 Hz, while discarding masker-dominant modulations from the mixture envelopes.

The combined effects of reverberation and noise on speech intelligibility by cochlear implant listeners.

OBJECTIVE: The purpose of this study is to assess the individual effect of reverberation and noise, as well as their combined effect, on speech intelligibility by cochlear implant (CI) users. DESIGN: Sentence stimuli corrupted by reverberation, noise, and reverberation + noise are presented to 11 CI listeners for word identification. They are tested in two reverberation conditions (T60 = 0.6 s, 0.8 s), two noise conditions (SNR = 5 dB, 10 dB), and four reverberation + noise conditions. STUDY SAMPLE: Eleven CI users participated. RESULTS: Results indicated that reverberation degrades speech intelligibility to a greater extent than additive noise (speech-shaped noise), at least for the SNR levels tested. The combined effects were greater than those introduced by either reverberation or noise alone. CONCLUSIONS: The effect of reverberation on speech intelligibility by CI users was found to be larger than that by noise. The results from the present study highlight the importance of testing CI users in reverberant conditions, since testing in noise-alone conditions might underestimate the difficulties they experience in their daily lives where reverberation and noise often coexist.

Tackling the combined effects of reverberation and masking noise using ideal channel selection.

PURPOSE: In this article, a new signal-processing algorithm is proposed and evaluated for the suppression of the combined effects of reverberation and noise. METHOD: The proposed algorithm decomposes, on a short-term basis (every 20 ms), the reverberant stimuli into a number of channels and retains only a subset of the channels satisfying a signal-to-reverberant ratio (SRR) criterion. The construction of this criterion assumes access to a priori knowledge of the target (anechoic) signal, and the aim of this study was to assess the full potential of the proposed channel-selection algorithm, assuming that this criterion could be estimated accurately. Listening tests with normal-hearing listeners were conducted to assess the performance of the proposed algorithm in highly reverberant conditions (T(60) = 1.0 s), which included additive noise at 0 and 5 dB signal-to-noise ratios (SNRs). RESULTS: A substantial gain in intelligibility was obtained in both reverberant and combined reverberant and noise conditions. The mean intelligibility scores improved by 44 and 33 percentage points at 0 and 5 dB SNR reverberation + noise conditions. Feature analysis of the consonant confusion matrices revealed that the transmission of voicing information was most negatively affected, followed by manner and place of articulation. CONCLUSIONS: The proposed algorithm produced substantial gains in intelligibility, and this benefit was attributed to the ability of the proposed SRR criterion to detect accurately voiced or unvoiced boundaries. It was postulated that detection of those boundaries is critical for better perception of voicing information and manner of articulation.

Development and validation of the AzBio sentence lists.

OBJECTIVES: The goal of this study was to create and validate a new set of sentence lists that could be used to evaluate the speech perception abilities of hearing-impaired listeners and cochlear implant (CI) users. Our intention was to generate a large number of sentence lists with an equivalent level of difficulty for the evaluation of performance over time and across conditions. DESIGN: The AzBio sentence corpus includes 1000 sentences recorded from two female and two male talkers. The mean intelligibility of each sentence was estimated by processing each sentence through a five-channel CI simulation and calculating the mean percent correct score achieved by 15 normal-hearing listeners. Sentences from each talker were sorted by percent correct score, and 165 sentences were selected from each talker and were then sequentially assigned to 33 lists, each containing 20 sentences (5 sentences from each talker). List equivalency was validated by presenting all lists, in random order, to 15 CI users. RESULTS: Using sentence scores from the CI simulation study produced 33 lists of sentences with a mean score of 85% correct. The results of the validation study with CI users revealed no significant differences in percent correct scores for 29 of the 33 sentence lists. However, individual listeners demonstrated considerable variability in performance on the 29 lists. The binomial distribution model was used to account for the inherent variability observed in the lists. This model was also used to generate 95% confidence intervals for one and two list comparisons. A retrospective analysis of 172 instances where research subjects had been tested on two lists within a single condition revealed that 94% of results were accurately contained within these confidence intervals. CONCLUSIONS: The use of a five-channel CI simulation to estimate the intelligibility of individual sentences allowed for the creation of a large number of sentence lists with an equivalent level of difficulty. The results of the validation procedure with CI users found that 29 of 33 lists allowed scores that were not statistically different. However, individual listeners demonstrated considerable variability in performance across lists. This variability was accurately described by the binomial distribution model and was used to estimate the magnitude of change required to achieve statistical significance when comparing scores from one and two lists per condition. Fifteen sentence lists have been included in the AzBio Sentence Test for use in the clinical evaluation of hearing-impaired listeners and CI users. An additional eight sentence lists have been included in the Minimum Speech Test Battery to be distributed by the CI manufacturers for the evaluation of CI candidates.

Adding real-time noise suppression capability to the cochlear implant PDA research platform.

This paper presents the real-time implementation of an environment-adaptive noise suppression algorithm on an FDA-approved PDA platform for cochlear implant studies. This added capability involves identifying the background noise environment in real-time and adapting a data-driven noise suppression approach to that noise environment on-the-fly. Various software optimization steps are taken in order to achieve a real-time throughput on the PDA platform involving both the speech decomposition and the adaptive noise suppression components. Real-time timing results and a quantitative measure of noise suppression are presented.

On the design and evaluation of the PDA-based research platform for electric and acoustic stimulation.

The aim of the paper is to describe the bimodal (combining electrical stimulation via the implant with acoustic stimulation via hearing aids) design of the PDA-based research platform and present results from a short-term evaluation with five bimodal cochlear implant users. The evolution of the PDA platform has been reported earlier in terms of development and its potential in various experiments. This paper focuses on the evaluation of the platform with bimodal users in terms of speech intelligibility in quiet, 10dB and 5dB SNR conditions and compares the results with the users' own clinical processor. The results of this clinical trial will encourage researchers in this area to use the platform in their future studies as it provides unparalleled flexibility along with a large suite of applications to conduct a wide variety of experiments for electric-only and combined electric and acoustic stimulation (EAS) for long-term chronic studies with great ease.