'In the world, but not of it': Exploring the impacts of hearing loss stigma

This seminar was delivered on 21st September 2011 by Dr Kenneth Southall from the Institut de recherche Élisabeth-Bruyère, affiliated with University of Ottawa, Canada. The presentation was hosted at Brunel University as part of the Brunel Institute for Bioengineering Seminar Series. A video of the presentation can be viewed at the link below

Efficacy in noise of the Starkey Surflink Mobile 2 technology in directional versus omnidirectional microphone mode with experienced adult hearing aid users

The Starkey SurfLink Mobile 2 is a remote microphone accessory. Starkey claims that by placing the SurfLink’s internal microphone in the directional microphone setting, the participant will hear better in noise over the omnidirectional setting. This study aims to test the thisthe claim about the devic

Effect of adaptive frequency lowering on phoneme identification and sound quality of music in hearing-impaired listeners

The most common type and configuration of hearing loss seen in clinics is high frequency sensorineural hearing loss. High-frequency hearing losses can lead to difficulties understanding speech in noise. Traditional amplification can aid in audibility of high-frequency information; however, its success is limited due to acoustic feedback, output limitations of the hearing aids, and loudness discomfort (Bohnert, Nyffeler, & Keilmann, 2010, Turner & Cummings, 1999). Cochlear dead regions further hinder the success of traditional hearing aids, as speech recognition may not improve with increased audibility (Turner & Cummings, 1999). Frequency-lowering algorithms, developed by four major hearing aid manufacturers, attempt to provide improved audibility and speech understanding. Several studies have assessed the success of this technology; however mixed results have been found. The current study’s purpose is to examine the effects of adaptive frequency lowering on phoneme identification and sound quality of music. Seven subjects with high frequency hearing loss were fit with Starkey Xino RITE hearing aids and were tested in two conditions (adaptive frequency lowering on and adaptive frequency lowering off). The Nonsense Syllable Test, Speech Perception In Noise test, and sound quality of music forced choice protocol were used to compare the two algorithms. The results of this study revealed no significant differences between traditional amplification and adaptive frequency lowering algorithm for identification of nonsense syllables, speech perception in noise, and preference of sound quality of music

Manipulation of Auditory Feedback in Individuals with Normal Hearing and Hearing Loss

Auditory feedback, the hearing of one’s own voice, plays an important role in the detection of speech errors and the regulation of speech production. The limited auditory cues available with a hearing loss can reduce the ability of individuals with hearing loss to use their auditory feedback. Hearing aids are a common assistive device that amplifies inaudible sounds. Hearing aids can also change auditory feedback through digital signal processing, such as frequency lowering. Frequency lowering moves high frequency information of an incoming auditory stimulus into a lower frequency region where audibility may be better. This can change how speech sounds are perceived. For example, the high frequency information of /s/ is moved closer to the lower frequency area of /ʃ/. As well, real-time signal processing in a laboratory setting can also manipulate various aspects of speech cues, such as intensity and vowel formants. These changes in auditory feedback may result in changes in speech production as the speech motor control system may perceive these perturbations as speech errors. A series of experiments were carried out to examine changes in speech production as a result of perturbations in the auditory feedback in individuals with normal hearing and hearing loss. Intensity and vowel formant perturbations were conducted using real-time signal processing in the laboratory. As well, changes in speech production were measured using auditory feedback that was processed with frequency lowering technology in hearing aids. Acoustic characteristics of intensity of vowels, sibilant fricatives, and first and second formants were analyzed. The results showed that the speech motor control system is sensitive to changes in auditory feedback because perturbations in auditory feedback can result in changes in speech production. However, speech production is not completely controlled by auditory feedback and other feedback systems, such as the somatosensory system, are also involved. An impairment of the auditory system can reduce the ability of the speech motor control system to use auditory feedback in the detection of speech errors, even when aided with hearing aids. Effects of frequency lowering in hearing aids on speech production depend on the parameters used and acclimatization time

The listening talker: A review of human and algorithmic context-induced modifications of speech

International audienceSpeech output technology is finding widespread application, including in scenarios where intelligibility might be compromised - at least for some listeners - by adverse conditions. Unlike most current algorithms, talkers continually adapt their speech patterns as a response to the immediate context of spoken communication, where the type of interlocutor and the environment are the dominant situational factors influencing speech production. Observations of talker behaviour can motivate the design of more robust speech output algorithms. Starting with a listener-oriented categorisation of possible goals for speech modification, this review article summarises the extensive set of behavioural findings related to human speech modification, identifies which factors appear to be beneficial, and goes on to examine previous computational attempts to improve intelligibility in noise. The review concludes by tabulating 46 speech modifications, many of which have yet to be perceptually or algorithmically evaluated. Consequently, the review provides a roadmap for future work in improving the robustness of speech output

Efficient calculation of sensor utility and sensor removal in wireless sensor networks for adaptive signal estimation and beamforming

Wireless sensor networks are often deployed over a large area of interest and therefore the quality of the sensor signals may vary significantly across the different sensors. In this case, it is useful to have a measure for the importance or the so-called "utility" of each sensor, e.g., for sensor subset selection, resource allocation or topology selection. In this paper, we consider the efficient calculation of sensor utility measures for four different signal estimation or beamforming algorithms in an adaptive context. We use the definition of sensor utility as the increase in cost (e.g., mean-squared error) when the sensor is removed from the estimation procedure. Since each possible sensor removal corresponds to a new estimation problem (involving less sensors), calculating the sensor utilities would require a continuous updating of different signal estimators (where is the number of sensors), increasing computational complexity and memory usage by a factor. However, we derive formulas to efficiently calculate all sensor utilities with hardly any increase in memory usage and computational complexity compared to the signal estimation algorithm already in place. When applied in adaptive signal estimation algorithms, this allows for on-line tracking of all the sensor utilities at almost no additional cost. Furthermore, we derive efficient formulas for sensor removal, i.e., for updating the signal estimator coefficients when a sensor is removed, e.g., due to a failure in the wireless link or when its utility is too low. We provide a complexity evaluation of the derived formulas, and demonstrate the significant reduction in computational complexity compared to straightforward implementations