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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

A PDA platform for offline processing and streaming of stimuli for cochlear implant research.

A PDA-based research platform has been developed for implementing novel speech processing strategies and conducting psychophysical experiments with cochlear implant (CI) research that do not necessarily require real-time processing. The developed interface streams stimuli pulses to a CI unit in an offline mode from a Personal Computer via PDA platform using Windows Sockets (WINSOCK). Front-end of the application is run in MATLAB where stimuli pulses are created.

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.

A Dual-Microphone Speech Enhancement Algorithm Based on the Coherence Function.

A novel dual-microphone speech enhancement technique is proposed in the present paper. The technique utilizes the coherence between the target and noise signals as a criterion for noise reduction and can be generally applied to arrays with closely-spaced microphones, where noise captured by the sensors is highly correlated. The proposed algorithm is simple to implement and requires no estimation of noise statistics.

Impact of SNR and Gain-Function Over- and Under-estimation on Speech Intelligibility.

Most noise reduction algorithms rely on obtaining reliable estimates of the SNR of each frequency bin. For that reason, much work has been done in analyzing the behavior and performance of SNR estimation algorithms in the context of improving speech quality and reducing speech distortions (e.g.

The effects of selective consonant amplification on sentence recognition in noise by hearing-impaired listeners.

Weak consonants (e.g., stops) are more susceptible to noise than vowels, owing partially to their lower intensity.

Reasons why current speech-enhancement algorithms do not improve speech intelligibility and suggested solutions.

Existing speech enhancement algorithms can improve speech quality but not speech intelligibility, and the reasons for that are unclear. In the present paper, we present a theoretical framework that can be used to analyze potential factors that can influence the intelligibility of processed speech. More specifically, this framework focuses on the fine-grain analysis of the distortions introduced by speech enhancement algorithms.

Gain-induced speech distortions and the absence of intelligibility benefit with existing noise-reduction algorithms.

Most noise-reduction algorithms used in hearing aids apply a gain to the noisy envelopes to reduce noise interference. The present study assesses the impact of two types of speech distortion introduced by noise-suppressive gain functions: amplification distortion occurring when the amplitude of the target signal is over-estimated, and attenuation distortion occurring when the target amplitude is under-estimated. Sentences corrupted by steady noise and competing talker were processed through a noise-reduction algorithm and synthesized to contain either amplification distortion, attenuation distortion or both.

The impact of reverberant self-masking and overlap-masking effects on speech intelligibility by cochlear implant listeners (L).

The purpose of this study is to determine the relative impact of reverberant self-masking and overlap-masking effects on speech intelligibility by cochlear implant listeners. Sentences were presented in two conditions wherein reverberant consonant segments were replaced with clean consonants, and in another condition wherein reverberant vowel segments were replaced with clean vowels. The underlying assumption is that self-masking effects would dominate in the first condition, whereas overlap-masking effects would dominate in the second condition.