Improvement of Speech Perception for Hearing-Impaired Listeners

Hearing impairment is becoming a prevalent health problem affecting 5% of world adult populations. Hearing aids and cochlear implant already play an essential role in helping patients over decades, but there are still several open problems that prevent them from providing the maximum benefits. Financial and discomfort reasons lead to only one of four patients choose to use hearing aids; Cochlear implant users always have trouble in understanding speech in a noisy environment. In this dissertation, we addressed the hearing aids limitations by proposing a new hearing aid signal processing system named Open-source Self-fitting Hearing Aids System (OS SF hearing aids). The proposed hearing aids system adopted the state-of-art digital signal processing technologies, combined with accurate hearing assessment and machine learning based self-fitting algorithm to further improve the speech perception and comfort for hearing aids users. Informal testing with hearing-impaired listeners showed that the testing results from the proposed system had less than 10 dB (by average) difference when compared with those results obtained from clinical audiometer. In addition, Sixteen-channel filter banks with adaptive differential microphone array provides up to six-dB SNR improvement in the noisy environment. Machine-learning based self-fitting algorithm provides more suitable hearing aids settings. To maximize cochlear implant users’ speech understanding in noise, the sequential (S) and parallel (P) coding strategies were proposed by integrating high-rate desynchronized pulse trains (DPT) in the continuous interleaved sampling (CIS) strategy. Ten participants with severe hearing loss participated in the two rounds cochlear implants testing. The testing results showed CIS-DPT-S strategy significantly improved (11%) the speech perception in background noise, while the CIS-DPT-P strategy had a significant improvement in both quiet (7%) and noisy (9%) environment

Biophysical modeling of a cochlear implant system: progress on closed-loop design using a novel patient-specific evaluation platform

The modern cochlear implant is one of the most successful neural stimulation devices, which partially mimics the workings of the auditory periphery. In the last few decades it has created a paradigm shift in hearing restoration of the deaf population, which has led to more than 324,000 cochlear implant users today. Despite its great success there is great disparity in patient outcomes without clear understanding of the aetiology of this variance in implant performance. Furthermore speech recognition in adverse conditions or music appreciation is still not attainable with today's commercial technology. This motivates the research for the next generation of cochlear implants that takes advantage of recent developments in electronics, neuroscience, nanotechnology, micro-mechanics, polymer chemistry and molecular biology to deliver high fidelity sound. The main difficulties in determining the root of the problem in the cases where the cochlear implant does not perform well are two fold: first there is not a clear paradigm on how the electrical stimulation is perceived as sound by the brain, and second there is limited understanding on the plasticity effects, or learning, of the brain in response to electrical stimulation. These significant knowledge limitations impede the design of novel cochlear implant technologies, as the technical specifications that can lead to better performing implants remain undefined. The motivation of the work presented in this thesis is to compare and contrast the cochlear implant neural stimulation with the operation of the physiological healthy auditory periphery up to the level of the auditory nerve. As such design of novel cochlear implant systems can become feasible by gaining insight on the question `how well does a specific cochlear implant system approximate the healthy auditory periphery?' circumventing the necessity of complete understanding of the brain's comprehension of patterned electrical stimulation delivered from a generic cochlear implant device. A computational model, termed Digital Cochlea Stimulation and Evaluation Tool (‘DiCoStET’) has been developed to provide an objective estimate of cochlear implant performance based on neuronal activation measures, such as vector strength and average activation. A patient-specific cochlea 3D geometry is generated using a model derived by a single anatomical measurement from a patient, using non-invasive high resolution computed tomography (HRCT), and anatomically invariant human metrics and relations. Human measurements of the neuron route within the inner ear enable an innervation pattern to be modelled which joins the space from the organ of Corti to the spiral ganglion subsequently descending into the auditory nerve bundle. An electrode is inserted in the cochlea at a depth that is determined by the user of the tool. The geometric relation between the stimulation sites on the electrode and the spiral ganglion are used to estimate an activating function that will be unique for the specific patient's cochlear shape and electrode placement. This `transfer function', so to speak, between electrode and spiral ganglion serves as a `digital patient' for validating novel cochlear implant systems. The novel computational tool is intended for use by bioengineers, surgeons, audiologists and neuroscientists alike. In addition to ‘DiCoStET’ a second computational model is presented in this thesis aiming at enhancing the understanding of the physiological mechanisms of hearing, specifically the workings of the auditory synapse. The purpose of this model is to provide insight on the sound encoding mechanisms of the synapse. A hypothetical mechanism is suggested in the release of neurotransmitter vesicles that permits the auditory synapse to encode temporal patterns of sound separately from sound intensity. DiCoStET was used to examine the performance of two different types of filters used for spectral analysis in the cochlear implant system, the Gammatone type filter and the Butterworth type filter. The model outputs suggest that the Gammatone type filter performs better than the Butterworth type filter. Furthermore two stimulation strategies, the Continuous Interleaved Stimulation (CIS) and Asynchronous Interleaved Stimulation (AIS) have been compared. The estimated neuronal stimulation spatiotemporal patterns for each strategy suggest that the overall stimulation pattern is not greatly affected by the temporal sequence change. However the finer detail of neuronal activation is different between the two strategies, and when compared to healthy neuronal activation patterns the conjecture is made that the sequential stimulation of CIS hinders the transmission of sound fine structure information to the brain. The effect of the two models developed is the feasibility of collaborative work emanating from various disciplines; especially electrical engineering, auditory physiology and neuroscience for the development of novel cochlear implant systems. This is achieved by using the concept of a `digital patient' whose artificial neuronal activation is compared to a healthy scenario in a computationally efficient manner to allow practical simulation times.Open Acces

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

Improving the Speech Intelligibility By Cochlear Implant Users

In this thesis, we focus on improving the intelligibility of speech for cochlear implants (CI) users. As an auditory prosthetic device, CI can restore hearing sensations for most patients with profound hearing loss in both ears in a quiet background. However, CI users still have serious problems in understanding speech in noisy and reverberant environments. Also, bandwidth limitation, missing temporal fine structures, and reduced spectral resolution due to a limited number of electrodes are other factors that raise the difficulty of hearing in noisy conditions for CI users, regardless of the type of noise. To mitigate these difficulties for CI listener, we investigate several contributing factors such as the effects of low harmonics on tone identification in natural and vocoded speech, the contribution of matched envelope dynamic range to the binaural benefits and contribution of low-frequency harmonics to tone identification in quiet and six-talker babble background. These results revealed several promising methods for improving speech intelligibility for CI patients. In addition, we investigate the benefits of voice conversion in improving speech intelligibility for CI users, which was motivated by an earlier study showing that familiarity with a talker’s voice can improve understanding of the conversation. Research has shown that when adults are familiar with someone’s voice, they can more accurately – and even more quickly – process and understand what the person is saying. This theory identified as the “familiar talker advantage” was our motivation to examine its effect on CI patients using voice conversion technique. In the present research, we propose a new method based on multi-channel voice conversion to improve the intelligibility of transformed speeches for CI patients

Auf einem menschlichen Gehörmodell basierende Elektrodenstimulationsstrategie für Cochleaimplantate

Cochleaimplantate (CI), verbunden mit einer professionellen Rehabilitation, haben mehreren hunderttausenden Hörgeschädigten die verbale Kommunikation wieder ermöglicht. Betrachtet man jedoch die Rehabilitationserfolge, so haben CI-Systeme inzwischen ihre Grenzen erreicht. Die Tatsache, dass die meisten CI-Träger nicht in der Lage sind, Musik zu genießen oder einer Konversation in geräuschvoller Umgebung zu folgen, zeigt, dass es noch Raum für Verbesserungen gibt.Diese Dissertation stellt die neue CI-Signalverarbeitungsstrategie Stimulation based on Auditory Modeling (SAM) vor, die vollständig auf einem Computermodell des menschlichen peripheren Hörsystems beruht.Im Rahmen der vorliegenden Arbeit wurde die SAM Strategie dreifach evaluiert: mit vereinfachten Wahrnehmungsmodellen von CI-Nutzern, mit fünf CI-Nutzern, und mit 27 Normalhörenden mittels eines akustischen Modells der CI-Wahrnehmung. Die Evaluationsergebnisse wurden stets mit Ergebnissen, die durch die Verwendung der Advanced Combination Encoder (ACE) Strategie ermittelt wurden, verglichen. ACE stellt die zurzeit verbreitetste Strategie dar. Erste Simulationen zeigten, dass die Sprachverständlichkeit mit SAM genauso gut wie mit ACE ist. Weiterhin lieferte SAM genauere binaurale Merkmale, was potentiell zu einer Verbesserung der Schallquellenlokalisierungfähigkeit führen kann. Die Simulationen zeigten ebenfalls einen erhöhten Anteil an zeitlichen Pitchinformationen, welche von SAM bereitgestellt wurden. Die Ergebnisse der nachfolgenden Pilotstudie mit fünf CI-Nutzern zeigten mehrere Vorteile von SAM auf. Erstens war eine signifikante Verbesserung der Tonhöhenunterscheidung bei Sinustönen und gesungenen Vokalen zu erkennen. Zweitens bestätigten CI-Nutzer, die kontralateral mit einem Hörgerät versorgt waren, eine natürlicheren Klangeindruck. Als ein sehr bedeutender Vorteil stellte sich drittens heraus, dass sich alle Testpersonen in sehr kurzer Zeit (ca. 10 bis 30 Minuten) an SAM gewöhnen konnten. Dies ist besonders wichtig, da typischerweise Wochen oder Monate nötig sind. Tests mit Normalhörenden lieferten weitere Nachweise für die verbesserte Tonhöhenunterscheidung mit SAM.Obwohl SAM noch keine marktreife Alternative ist, versucht sie den Weg für zukünftige Strategien, die auf Gehörmodellen beruhen, zu ebnen und ist somit ein erfolgversprechender Kandidat für weitere Forschungsarbeiten.Cochlear implants (CIs) combined with professional rehabilitation have enabled several hundreds of thousands of hearing-impaired individuals to re-enter the world of verbal communication. Though very successful, current CI systems seem to have reached their peak potential. The fact that most recipients claim not to enjoy listening to music and are not capable of carrying on a conversation in noisy or reverberative environments shows that there is still room for improvement.This dissertation presents a new cochlear implant signal processing strategy called Stimulation based on Auditory Modeling (SAM), which is completely based on a computational model of the human peripheral auditory system.SAM has been evaluated through simplified models of CI listeners, with five cochlear implant users, and with 27 normal-hearing subjects using an acoustic model of CI perception. Results have always been compared to those acquired using Advanced Combination Encoder (ACE), which is today’s most prevalent CI strategy. First simulations showed that speech intelligibility of CI users fitted with SAM should be just as good as that of CI listeners fitted with ACE. Furthermore, it has been shown that SAM provides more accurate binaural cues, which can potentially enhance the sound source localization ability of bilaterally fitted implantees. Simulations have also revealed an increased amount of temporal pitch information provided by SAM. The subsequent pilot study, which ran smoothly, revealed several benefits of using SAM. First, there was a significant improvement in pitch discrimination of pure tones and sung vowels. Second, CI users fitted with a contralateral hearing aid reported a more natural sound of both speech and music. Third, all subjects were accustomed to SAM in a very short period of time (in the order of 10 to 30 minutes), which is particularly important given that a successful CI strategy change typically takes weeks to months. An additional test with 27 normal-hearing listeners using an acoustic model of CI perception delivered further evidence for improved pitch discrimination ability with SAM as compared to ACE.Although SAM is not yet a market-ready alternative, it strives to pave the way for future strategies based on auditory models and it is a promising candidate for further research and investigation

Implant technology and TFS processing in relation to speech discrimination and music perception and appreciation

Direct stimulation of the auditory nerve via a Cochlear Implant (CI) enables profoundly deaf subjects to perceive sounds. Many CI users find language comprehension satisfactory in quiet and accessible in the presence of noise. However, music contains different dimensions which need to be approached in different ways. Whilst both language and music take advantage of the modulation of acoustic parameters to convey information, music is an acoustically more complex stimulus than language, demanding more complex resolution mechanisms. One of the most important aspects that contributes to speech perception skills, especially when listening in a fluctuating background, is Temporal Fine Structure processing. TFS cues are pre-dominant in conveying Low Frequency (LF) signals. Harmonic (HI) and Disharmonic (DI) In-tonation are tests of pitch perception in the LF domain which are thought to depend on avail-ability of TFS cues and which are included in the protocol on this group of adult CI recipients. One of the primary aims of this thesis was the production of a new assessment tool, the Italian STARR test which was based on the measurement of speech perception using a roving-level adaptive method where the presentation level of both speech and noise signals varied between each sentence presentation. The STARR test attempts to reflect a better representation of real world listening conditions where background noise is usually present and speech intensity var-ies according to vocal capacity as well as the distance of the speaker. The outcomes for the Italian STARR in NH adults were studied to produce normative data, as well as to evaluate inter-list variability and learning effects. (Chapter 4). The second aim was to investigate LF pitch perception outcomes linked to availability of TFS cues in a group of adult CI recipients including bimodal users in relation to speech perception, in particular Italian STARR outcomes. Here it was seen that age had a significant effect on performance especially in older adults. Similarly, CI recipients (even better performers) showed abnormal findings in comparison to NH subjects. On the other hand, the significant effect of CI thresholds re-emphasized the sensitivity of the test to low intensity speech which a CI user can often encounter under everyday listening conditions. Statistically significant correlations between HI/DI and STARR performance were found. Moreover, bimodal benefit was seen both for HI/DI and STARR tests. Overall findings confirmed the usefulness of evaluating both LF pitch and speech perception in noise in order to track changes in TFS sen-sitivity for CI recipients over time and across different listening conditions which might be provided by future technological progress. (Chapter 5) Finally, the last and main aspect taken into account in this thesis was the study of the difficul-ties experienced by CI users when listening to music. An attempt was made to correlate find-ings resulting from the previous phases of this study both to Speech in Noise and to the com-plex subjective aspects of Music Perception and Appreciation: correlation analysis between HI/DI tests and the main dimensions of Speech in Noise (STARR and OLSA) and Music Ap-preciation was performed. (Chapter 6). Interestingly, positive findings were found for the two most complex types of Music (Classical, Jazz), whereas Soul did not seem to require particular competence in Pitch perception for the appreciation of the subjective variables taken into con-sideration by this study

The use of acoustic cues in phonetic perception: Effects of spectral degradation, limited bandwidth and background noise

Hearing impairment, cochlear implantation, background noise and other auditory degradations result in the loss or distortion of sound information thought to be critical to speech perception. In many cases, listeners can still identify speech sounds despite degradations, but understanding of how this is accomplished is incomplete. Experiments presented here tested the hypothesis that listeners would utilize acoustic-phonetic cues differently if one or more cues were degraded by hearing impairment or simulated hearing impairment. Results supported this hypothesis for various listening conditions that are directly relevant for clinical populations. Analysis included mixed-effects logistic modeling of contributions of individual acoustic cues for various contrasts. Listeners with cochlear implants (CIs) or normal-hearing (NH) listeners in CI simulations showed increased use of acoustic cues in the temporal domain and decreased use of cues in the spectral domain for the tense/lax vowel contrast and the word-final fricative voicing contrast. For the word-initial stop voicing contrast, NH listeners made less use of voice-onset time and greater use of voice pitch in conditions that simulated high-frequency hearing impairment and/or masking noise; influence of these cues was further modulated by consonant place of articulation. A pair of experiments measured phonetic context effects for the "s/sh" contrast, replicating previously observed effects for NH listeners and generalizing them to CI listeners as well, despite known deficiencies in spectral resolution for CI listeners. For NH listeners in CI simulations, these context effects were absent or negligible. Audio-visual delivery of this experiment revealed enhanced influence of visual lip-rounding cues for CI listeners and NH listeners in CI simulations. Additionally, CI listeners demonstrated that visual cues to gender influence phonetic perception in a manner consistent with gender-related voice acoustics. All of these results suggest that listeners are able to accommodate challenging listening situations by capitalizing on the natural (multimodal) covariance in speech signals. Additionally, these results imply that there are potential differences in speech perception by NH listeners and listeners with hearing impairment that would be overlooked by traditional word recognition or consonant confusion matrix analysis

Temporal fine structure processing, pitch and speech perception in cochlear implant recipients

Cochlear implant (CI) recipients usually complain about poor speech understanding in the presence of noise. Indeed, they generally show ceiling effects for understanding sentences presented in quiet, but their scores decrease drastically when testing in the presence of competing noise. One important aspect that contributes to speech perception skills, especially when listening in a fluctuating background, has been described as Temporal Fine Structure (TFS) processing. TFS cues are more dominant in conveying Low Frequency (LF) signals linked in particular to Fundamental Frequency (F0), which is crucial for linguistic and musical perception. A§E Harmonic Intonation (HI) and Disharmonic Intonation (DI) are tests of pitch perception in the LF domain and their outcomes are believed to depend on the availability of TFS cues. Previous findings indicated that the DI test provided more differential LF pitch perception outcomes in that it reflected phase locking and TFS processing capacities of the ear, whereas the HI test provided information on its place coding capacity as well. Previous HI/DI studies were mainly done in adult population showing abnormal pitch perception outcomes in CI recipients and there was no or limited data in paediatric population as well as HI/DI outcomes in relation to speech perception outcomes in the presence of noise. One of the primary objectives of this thesis has been to investigate LF pitch perception skills in a group of pediatric CI recipients in comparison to normal hearing (NH) children. Another objective was to introduce a new assessment tool, the Italian STARR test which was based on measurement of speech perception using a roving-level adaptive method where the presentation level of both speech and noise signals varied across sentences. The STARR test attempts to reflect a better representation of real world listening conditions where background noise is usually present and speech intensity varies according to vocal capacity as well as the distance of the speaker. The Italian STARR outcomes in NH adults were studied to produce normative data, as well as to evaluate interlist variability and learning effects. Finally, LF pitch perception outcomes linked to availability of TFS were investigated in a group of adult CI recipients including bimodal users in relation to speech perception, in particular Italian STARR outcomes. Results were interesting: Although the majority of CI recipient children showed abnormal outcomes for A§E, their scores were considerably better than in the adult CI users. Age had a statistically significant effect on performance in both children and adults; younger children and older adults tended to show poorer performance. Similarly, CI recipient adults (even the better performers) showed abnormal STARR outcomes in comparison to NH subjects and group differences were statistically significant. The duration of profound deafness before implantation had a significant effect on STARR performance. On the other hand, the significant effect of CI thresholds re-emphasized the sensitivity of the test to lower level speech which a CI user can face very often during everyday life. Analysis revealed statistically significant correlations between HI/DI and STARR performance. Moreover, contralateral hearing aid users showed significant bimodal benefit for both HI/DI and STARR tests. Overall findings confirmed the usefulness of evaluating both LF pitch and speech perception in order to track changes in TFS sensitivity for CI recipients over time and across different listening conditions which might be provided by future technological advances as well as to study individual differences