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

Compression and amplification algorithms in hearing aids impair the selectivity of neural responses to speech

In quiet environments, hearing aids improve the perception of low-intensity sounds. However, for high-intensity sounds in background noise, the aids often fail to provide a benefit to the wearer. Here, using large-scale single-neuron recordings from hearing-impaired gerbils—an established animal model of human hearing—we show that hearing aids restore the sensitivity of neural responses to speech, but not their selectivity. Rather than reflecting a deficit in supra-threshold auditory processing, the low selectivity is a consequence of hearing-aid compression (which decreases the spectral and temporal contrasts of incoming sound) and amplification (which distorts neural responses, regardless of whether hearing is impaired). Processing strategies that avoid the trade-off between neural sensitivity and selectivity should improve the performance of hearing aids

FPGA Implementation of Hearing Impaired Assistive Device for Hard to Hear Individuals

The Noise cancellation and suppression techniques have been developed and implemented in field-programmable gate array (FPGA) in this work. Hearing aids are primarily meant for improving hearing and speech comprehensions. Digital hearing aids score over their analog counterparts. This happens as digital hearing aids provide flexible gain besides facilitating feedback reduction and noise elimination. Recent advances in digital signal processors (DSP) and Microelectronics have led to the development of superior digital hearing aids. Many researchers have investigated several algorithms suitable for hearing aid application that demands low noise, feed-back cancellation, echo cancellation, etc., however the toughest challenge is the implementation. Furthermore, the additional constraints are power and area. The device must consume as minimum power as possible to support extended battery life and should be as small as possible for increased portability. In this work, we are using cross-channel suppression technique to remove the unwanted audio signals. The unwanted signals are suppressed using twotone suppression scheme. In this project, the speech signal is absorbed by microphone. This signal is then converted to digital using ADC. The digitized signal is processed using FPGA. Here in FPGA the speech signal is enhanced and amplified to the desired level. The processed speech signal is then converted into analog format using DAC and is given to speaker

Sounds in noise: Behavioral and neural studies of illusory continuity and discontinuity

ability to parse an auditory scene into meaningful components varies greatly between individuals; some are able to parse out and write down competing musical pieces while others struggle to understand each word whenever they have to converse in a noisy environment. Using a simple discrimination task, healthy, normally-heari ng adult participants were asked to judge whether a pure tone (with or without amplitude modulation) was continuous or contained a gap. One quarter of the participants consistently heard a gap when none was present, if the tone was accompanied by a higher-frequency noise burst with a lower edge beginning one octave away from the tone (that did not have any energy overlapping the tone). This novel form of informational masking (perceptual interference between components with non-overlapping sound energy) was named 'illusory auditory discontinuity\u2019. The phenomenon appears to reflect natural differences in auditory processing rather than differences in decision-making strategies because: (1) susceptibility to illusory discontinuity correlates with individual differences in auditory streaming (measured using a classical ABA sequential paradigm); and (2) electroencephalographic responses elicited by tones overlaid by short noise bursts (when these sounds are not the focus of attention) are significantly correlated with the occurrence of illusory auditory discontinuity in both an early event-related potential (ERP) component (40-66 ms), and a later ERP component (270-350 ms) after noise onset. Participants prone to illusory discontinuity also tended not to perceive the \u2018auditory continuity illusion\u2019 (in which a tone is heard continuing under a burst of noise centered on the tone frequency that completely masks it) at short noise durations, but reliably perceived the auditory continuity illusion at longer noise durations. These results suggest that a number of attributes describing how individuals differentially parse complex auditory scenes are related to individual differences in two potentially independent attributes of neural processing, reflected here by EEG waveform differences at ~50 msec and ~300 msec after noise onset. Neural correlates of the auditory continuity illusion were also investigated by adjusting masker loudness, so that when listeners were given physically identical stimuli, they correctly detected the gap in a target tone on some trials, while on other trials they reported the tone as continuous (experiencing illusory continuity). High er power of low-frequency EEG activity (in the delta-theta range, <6 Hz) was observed prior to the onset of tones that were subsequently judged as discontinuous, with no other consistent EEG differences found after the onset of tones. These data suggest that the occurrence of the continuity illusion may depend on the brain state that exists immediately before a trial begins

Why Do Hearing Aids Fail to Restore Normal Auditory Perception?

Hearing loss is a widespread condition that is linked to declines in quality of life and mental health. Hearing aids remain the treatment of choice, but, unfortunately, even state-of-the-art devices provide only limited benefit for the perception of speech in noisy environments. While traditionally viewed primarily a loss of sensitivity, it is now clear that hearing loss has additional effects that cause complex distortions of sound-evoked neural activity that cannot be corrected by amplification alone. Here we describe the effects of hearing loss on neural activity in order to illustrate the reasons why current hearing aids are insufficient and to motivate the use of new technologies to explore directions for improving the next generation of devices

EFFICACY OF THREE BACKWARD MASKING SIGNALS

Increased backward masking has been correlated with Auditory Processing Disorders (APD). An efficacious test of the backward masking function that is compatible with naïve listeners could have clinical utility in diagnosing APDs. In order to determine an appropriate probe for such a test, three 20-ms signal-types were compared for ease-of-task. Response times (RT) were taken as a proxy for ease-of-task. Seven participants used a method-of-adjustment to track threshold in the presence of a 50-ms broadband-Gausian-noise backward-masker. The signal-types yielded two comparisons: Linear rise-fall on a 1000Hz sine-wave versus a “chirp” (750 Hz-4000Hz); Linear rise-fall vs Blackman gating function on a 1000Hz sine-wave. The results suggest that signal-type is a significant factor in participant response time and hence, confidence. Moreover, the contribution of signal-type to RT is not confounded by any potential interaction terms, such as inter-stimulus interval (ISI). The signal-type that yielded the quickest RTs across all participants, ISIs, and intensity levels was the 20-ms, 1000 Hz sine-wave fitted with a trapezoidal gating function. This may be the most efficacious signal-type to serve as a probe in a clinical test of backward masking

Predicting Speech Intelligibility

Hearing impairment, and specifically sensorineural hearing loss, is an increasingly prevalent condition, especially amongst the ageing population. It occurs primarily as a result of damage to hair cells that act as sound receptors in the inner ear and causes a variety of hearing perception problems, most notably a reduction in speech intelligibility. Accurate diagnosis of hearing impairments is a time consuming process and is complicated by the reliance on indirect measurements based on patient feedback due to the inaccessible nature of the inner ear. The challenges of designing hearing aids to counteract sensorineural hearing losses are further compounded by the wide range of severities and symptoms experienced by hearing impaired listeners. Computer models of the auditory periphery have been developed, based on phenomenological measurements from auditory-nerve fibres using a range of test sounds and varied conditions. It has been demonstrated that auditory-nerve representations of vowels in normal and noisedamaged ears can be ranked by a subjective visual inspection of how the impaired representations differ from the normal. This thesis seeks to expand on this procedure to use full word tests rather than single vowels, and to replace manual inspection with an automated approach using a quantitative measure. It presents a measure that can predict speech intelligibility in a consistent and reproducible manner. This new approach has practical applications as it could allow speechprocessing algorithms for hearing aids to be objectively tested in early stage development without having to resort to extensive human trials. Simulated hearing tests were carried out by substituting real listeners with the auditory model. A range of signal processing techniques were used to measure the model’s auditory-nerve outputs by presenting them spectro-temporally as neurograms. A neurogram similarity index measure (NSIM) was developed that allowed the impaired outputs to be compared to a reference output from a normal hearing listener simulation. A simulated listener test was developed, using standard listener test material, and was validated for predicting normal hearing speech intelligibility in quiet and noisy conditions. Two types of neurograms were assessed: temporal fine structure (TFS) which retained spike timing information; and average discharge rate or temporal envelope (ENV). Tests were carried out to simulate a wide range of sensorineural hearing losses and the results were compared to real listeners’ unaided and aided performance. Simulations to predict speech intelligibility performance of NAL-RP and DSL 4.0 hearing aid fitting algorithms were undertaken. The NAL-RP hearing aid fitting algorithm was adapted using a chimaera sound algorithm which aimed to improve the TFS speech cues available to aided hearing impaired listeners. NSIM was shown to quantitatively rank neurograms with better performance than a relative mean squared error and other similar metrics. Simulated performance intensity functions predicted speech intelligibility for normal and hearing impaired listeners. The simulated listener tests demonstrated that NAL-RP and DSL 4.0 performed with similar speech intelligibility restoration levels. Using NSIM and a computational model of the auditory periphery, speech intelligibility can be predicted for both normal and hearing impaired listeners and novel hearing aids can be rapidly prototyped and evaluated prior to real listener tests

Neural dynamics of selective attention to speech in noise

This thesis investigates how the neural system instantiates selective attention to speech in challenging acoustic conditions, such as spectral degradation and the presence of background noise. Four studies using behavioural measures, magneto- and electroencephalography (M/EEG) recordings were conducted in younger (20–30 years) and older participants (60–80 years). The overall results can be summarized as follows. An EEG experiment demonstrated that slow negative potentials reflect participants’ enhanced allocation of attention when they are faced with more degraded acoustics. This basic mechanism of attention allocation was preserved at an older age. A follow-up experiment in younger listeners indicated that attention allocation can be further enhanced in a context of increased task-relevance through monetary incentives. A subsequent study focused on brain oscillatory dynamics in a demanding speech comprehension task. The power of neural alpha oscillations (~10 Hz) reflected a decrease in demands on attention with increasing acoustic detail and critically also with increasing predictiveness of the upcoming speech content. Older listeners’ behavioural responses and alpha power dynamics were stronger affected by acoustic detail compared with younger listeners, indicating that selective attention at an older age is particularly dependent on the sensory input signal. An additional analysis of listeners’ neural phase-locking to the temporal envelopes of attended speech and unattended background speech revealed that younger and older listeners show a similar segregation of attended and unattended speech on a neural level. A dichotic listening experiment in the MEG aimed at investigating how neural alpha oscillations support selective attention to speech. Lateralized alpha power modulations in parietal and auditory cortex regions predicted listeners’ focus of attention (i.e., left vs right). This suggests that alpha oscillations implement an attentional filter mechanism to enhance the signal and to suppress noise. A final behavioural study asked whether acoustic and semantic aspects of task-irrelevant speech determine how much it interferes with attention to task-relevant speech. Results demonstrated that younger and older adults were more distracted when acoustic detail of irrelevant speech was enhanced, whereas predictiveness of irrelevant speech had no effect. All findings of this thesis are integrated in an initial framework for the role of attention for speech comprehension under demanding acoustic conditions