Browsing by Author "Akbarzadeh, Sara"
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Item A Speech Processing Strategy Based on Sinusoidal Speech Model for Cochlear Implant Users(Institute of Electrical and Electronics Engineers Inc.) Lee, Sungmin; Akbarzadeh, Sara; Singh, Satnam; Tan, Chin-Tuan; 0000-0002-4676-4917 (Tan, C-T); 78509491 (Tan, C-T); Lee, Sungmin; Akbarzadeh, Sara; Singh, Satnam; Tan, Chin-TuanIn sinusoidal modeling (SM), speech signal, which is pseudo-periodic in structure, can be approximated by sinusoids and noise without losing significant speech information. A speech processing strategy based on this sinusoidal speech model will be relevant for encoding electric pulse streams in cochlear implant (CI) processing, where the number of channels available is limited. In this study, 5 normal hearing (NH) listeners and 2 CI users were asked to perform the task of speech recognition and perceived sound quality rating on speech sentences processed in 12 different test conditions. The sinusoidal analysis/synthesis algorithm was limited to 1, 3 or 6 sinusoids from the sentences low-pass filtered at either 1 kHz, 1.5 kHz, 3 kHz, or 6 kHz, re-synthesized as the test conditions. Each of 12 lists of AzBio sentences was randomly chosen and process with one of 12 test conditions, before they were presented to each participant at 65 dB SPL (Sound Pressure Level). Participant was instructed to repeat the sentence as they perceived, and the number of words correctly recognized was scored. They were also asked to rate the perceived sound quality of the sentences including original speech sentence, on the scale of 1 (distorted) to 10 (clean). Both speech recognition score and perceived sound quality rating across all participants increase when the number of sinusoids increases and low-pass filter broadens. Our current finding showed that three sinusoids may be sufficient to elicit the nearly maximum speech intelligibility and quality necessary for both NH and CI listeners. Sinusoidal speech model has the potential in facilitating the basis for a speech processing strategy in CI. ©2018 APSIPA.Item Implication of Speech Level Control in Noise to Sound Quality Judgement(Institute of Electrical and Electronics Engineers Inc.) Akbarzadeh, Sara; Lee, Sungman; Singh, Satnam; Tan, Chin-Tuan; 0000-0002-4676-4917 (Tan, C-T); 78509491 (Tan, C-T); Akbarzadeh, Sara; Lee, Sungman; Singh, Satnam; Tan, Chin-TuanRelative levels of speech and noise, which is signal-to-noise ratio (SNR), alone as a metric may not fully account how human perceives speech in noise or making judgement on the sound quality of the speech component. To date, the most common rationale in front-end processing of noisy speech in assistive hearing devices is to reduce 'noise' (estimated) with a sole objective to improve the overall SNR. Absolute sound pressure level of speech in the remaining noise, which is necessary for listeners to anchor their perceptual judgement, is assumed to be restored by the subsequent dynamic range compression stage intended to compensate for the loudness recruitment in hearing impaired (HI). However, un-coordinated setting of thresholds that trigger the nonlinear processing in these two separate stages, amplify the remaining 'noise' and/or distortion instead. This will confuse listener's judgement of sound quality and deviate from the usual perceptual trend as one would expect when more noise was present. In this study, both normal hearing (NH) and HI listeners were asked to rate the sound quality of noisy speech and noise reduced speech as they perceived. The result found that speech processed by noise reduction algorithms were lower in quality compared to original unprocessed speech in noise conditions. The outcomes also showed that sound quality judgement was dependent on both input SNR and absolute level of speech, with a greater weightage on the latter, across both NH and HI listeners. The outcome of this study potentially suggests that integrating the two separate processing stages into one will better match with the underlying mechanism in auditory reception of sound. Further work will attempt to identify settings of these two processing stages for a better speech reception in assistive hearing device users. ©2018 APSIPA.Item Speech Perception of Hearing-impaired Listeners in Challenging Listening Environments and Personalization of Hearing Assistive Devices via Inverse Reinforcement Learning(2022-05-01T05:00:00.000Z) Akbarzadeh, Sara; Kehtarnavaz, Nasser; Tan, Chin-Tuan; Auciello, Orlando; Lobarinas, Edward; Tamil, LakshmanListening to a speech in presence of a noise has always been a challenge specially for individuals with hearing impairment. There are many aspects that needs to be considered in designing and fitting of hearing assistive devices to provide users with a more preferred hearing experience or increase the perceived quality of speech and decrease the listening effort. This dissertation focuses on this topic in two major research thrust. In the first research thrust, the speech perception of hearing impaired listeners has been studied in challenging hearing environments. Behavioral and electrophysiological experiments have been designed to evaluate the effect of speech and noise levels on the perceived quality of speech and selective auditory attention in normal hearing and hearing impaired listeners. The perception of degraded speeches in normal hearing and hearing impaired listeners have been measured and the differences between the hearing patterns in these groups have been described. It has been shown that to achieve an optimal hearing experience, the listener’s hearing situation should be taken into account. In the second research thrust, the maximum likelihood inverse reinforcement learning approach has been followed to develop an algorithm to personalize the hearing aids fitting in an online manner. The results of the experiments conducted on subjects with hearing loss demonstrates the outperformance of the developed personalized setting over the standard prescriptive setting.Item Wavelet Scattering Transform for Variability Reduction in Cortical Potentials Evoked by Pitch Matched Electro-Acoustic Stimulation in Unilateral Cochlear Implant Patients(Institute of Electrical and Electronics Engineers Inc.) Heydarzadeh, Mehrdad; Akbarzadeh, Sara; Tan, Chin-Tuan; 0000-0002-4676-4917 (Tan, C-T); 78509491 (Tan, C-T); Heydarzadeh, Mehrdad; Akbarzadeh, Sara; Tan, Chin-TuanCochlear implant (CI) restores the hearing sensation in profoundly deafen patients by directly stimulating auditory nerve with electric pulses using an array of tonotopically inserted electrodes. Basal electrodes stimulate in response to high input frequencies while apical electrodes stimulate to low input frequencies. The problem with this electrical stimulation, particularly in unilaterally implanted users who has residual hearing in the contra-lateral ear, lies in the frequency mismatch between characteristic frequency of auditory nerve and input signal. In this paper, we revisit our previously proposed mechanism for tuning intra-cochlear electrode to its pitch matched frequency using a single channel EEG [1]. We apply the wavelet scattering transform to extract a deformation invariant from the EEG signal recorded from each of 10 CI subjects when they were listening to pitch matched electro-acoustic stimulation. Results show that the wavelet scattering transform is able to capture the variability introduced by different subjects, and a more robust alternative to reveal the underlying neuro-physiological responses to this perceptual event. ©2018 APSIPA