Starr

Boyle, Patrick J.; Nunn, Terry; O’Connor, Alec Fitzgerald; Moore, Brian C. J.

doi:10.1097/aud.0b013e31826a8e82

Cited by 34 publications

(7 citation statements)

References 41 publications

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“…Due to the high transient peak levels and the high ''transient-to-speechratio'' of at least 22 dB in our experiment, the AGC attenuated the speech level to just below 50 dB SPL. At this speech level, average speech intelligibility in noise for CI users is relatively low at 20%, according to Boyle, Nunn, and O'Connor (2013). Our results differ from the findings of Stobich, Zierhofer, and Hochmair (1999) who reported word scores between 50 and 60% for speech with a transient and different AGC configurations.…”

Section: Effects Of Transients and Need For Tnrcontrasting

confidence: 57%

Effects of a transient noise reduction algorithm on speech intelligibility in noise, noise tolerance and perceived annoyance in cochlear implant users

Dingemanse

Vroegop

Goedegebure

2018

International Journal of Audiology

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Objective: To evaluate the validity and efficacy of a transient noise reduction algorithm (TNR) in cochlear implant processing and the interaction of TNR with a continuous noise reduction algorithm (CNR). Design: We studied the effects of TNR and CNR on the perception of realistic sound samples with transients, using subjective ratings of annoyance, a speech-in-noise test and a noise tolerance test. Study sample: Participants were 16 experienced cochlear implant recipients wearing an Advanced Bionics Naida Q70 processor. Results: CI users rated sounds with transients as moderately annoying. Annoyance was slightly, but significantly reduced by TNR. Transients caused a large decrease in speech intelligibility in noise and a moderate decrease in noise tolerance, measured on the Acceptable Noise Level test. The TNR had no significant effect on noise tolerance or on speech intelligibility in noise. The combined application of TNR and CNR did not result in interactions. Conclusions: The TNR algorithm was effective in reducing annoyance from transient sounds, but was not able to prevent a decreasing effect of transients on speech understanding in noise and noise tolerance. TNR did not reduce the beneficial effect of CNR on speech intelligibility in noise, but no cumulated improvement was found either.

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Section: Effects Of Transients and Need For Tnrcontrasting

confidence: 57%

Effects of a transient noise reduction algorithm on speech intelligibility in noise, noise tolerance and perceived annoyance in cochlear implant users

Dingemanse

Vroegop

Goedegebure

2018

International Journal of Audiology

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“…On average, the relative improvements predicted by STOI and NCM were 38% for the DNN and 46% for the RNN, indicating an advantage of the RNN of about 8 percentage points. It should be noted that the RNN provided the largest benefit over the DNN of about 15 percentage points on average for the SNR of 10 dB, which represents a condition that is challenging for many CI users (Boyle et al ., 2013; Goehring et al ., 2017; Croghan and Smith, 2018).…”

Section: Algorithm Descriptionmentioning

confidence: 99%

Using recurrent neural networks to improve the perception of speech in non-stationary noise by people with cochlear implants

Goehring

Keshavarzi

Carlyon

et al. 2019

The Journal of the Acoustical Society of America

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Speech-in-noise perception is a major problem for users of cochlear implants (CIs), especially with non-stationary background noise. Noise-reduction algorithms have produced benefits but relied on a priori information about the target speaker and/or background noise. We developed a recurrent neural network (RNN) algorithm for enhancing speech in non-stationary noise and evaluated its benefits for speech perception, using both objective measures and experiments with CI simulations and CI users. The RNN was trained using speech from many talkers mixed with multi-talker or traffic noise recordings. Its performance was evaluated using speech from a novel talker mixed with novel noise recordings of the same class, either babble or traffic noise. Objective measures indicated benefits of using a recurrent over a feed-forward architecture and predicted better speech intelligibility with than without the processing. The experimental results showed significantly improved intelligibility of speech in babble noise but not in traffic noise. CI subjects rated the processed stimuli as significantly better in terms of speech distortions, noise intrusiveness and overall quality than unprocessed stimuli for both babble and traffic noise. These results extend previous findings for CI users to mostly unseen acoustic conditions with non-stationary noise.

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“…Specifically, speech perception measured in the clinic is a commonly used hearing aid outcome within the field of audiology. Some speech perception tasks include competing background noise (e.g., Kalikow et al, 1977; Nilsson et al, 1994; Killion et al, 2004), varying amounts of semantic context (e.g., Kalikow et al, 1977), visual cues (e.g., Cox et al, 1989), or fluctuating stimulus presentation levels (Boyle et al, 2013) to better approximate real-world listening environments. However, it is not feasible in a clinical setting to represent the broad range of complex listening environments encountered on a daily basis outside the clinic.…”

Section: Introductionmentioning

confidence: 99%

Using a Digital Language Processor to Quantify the Auditory Environment and the Effect of Hearing Aids for Adults with Hearing Loss

Klein

Stangl

et al. 2018

J Am Acad Audiol

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Background Auditory environments can influence the communication function of individuals with hearing loss and the effects of hearing aids. Therefore, a tool that can objectively characterize a patient’s real-world auditory environments is needed. Purpose To use the Language Environment Analysis (LENA) system to quantify the auditory environments of adults with hearing loss, to examine if the use of hearing aids changes a user’s auditory environment, and to determine the association between LENA variables and self-report hearing aid outcome measures. Research Design This study used a crossover design. Study Sample Participants included 22 adults with mild-to-moderate hearing loss, age 64–82 yr. Intervention Participants were fitted with bilateral behind-the-ear hearing aids from a major manufacturer. Data Collection and Analysis The LENA system consists of a digital language processor (DLP) that is worn by an individual and records up to 16 hr of the individual’s auditory environment. The recording is then automatically categorized according to time spent in different types of auditory environments (e.g., meaningful speech and TV/electronic sound) by the LENA algorithms. The LENA system also characterizes the user’s auditory environment by providing the sound levels of different auditory categories. Participants in the present study wore a LENA DLP in an unaided condition and aided condition, which each lasted six to eight days. Participants wore bilateral hearing aids in the aided condition. Percentage of time spent in each auditory environment, as well as median levels of TV/electronic sounds and speech, were compared between subjects’ unaided and aided conditions using paired sample t tests. LENA data were also compared to self-report measures of hearing disability and hearing aid benefit using Pearson correlations. Results Overall, participants spent the greatest percentage of time in silence (~40%), relative to other auditory environments. Participants spent ~12% and 26% of their time in meaningful speech and TV/electronic sound environments, respectively. No significant differences were found between mean percentage of time spent in each auditory environment in the unaided and aided conditions. Median TV/electronic sound levels were on average 2.4 dB lower in the aided condition than in the unaided condition; speech levels were not significantly different between the two conditions. TV/electronic sound and speech levels did not significantly correlate with self-report data. Conclusions The LENA system can provide rich data to characterize the everyday auditory environments of older adults with hearing loss. Although TV/electronic sound level was significantly lower in the aided than unaided condition, the use of hearing aids seemed not to substantially change users’ auditory environments. Because there is no significant association between objective LENA variables and self-report questionnaire outcomes, these two types of measures may assess different aspects of communication function. The f...

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Starr

Cited by 34 publications

References 41 publications

Effects of a transient noise reduction algorithm on speech intelligibility in noise, noise tolerance and perceived annoyance in cochlear implant users

Effects of a transient noise reduction algorithm on speech intelligibility in noise, noise tolerance and perceived annoyance in cochlear implant users

Using recurrent neural networks to improve the perception of speech in non-stationary noise by people with cochlear implants

Using a Digital Language Processor to Quantify the Auditory Environment and the Effect of Hearing Aids for Adults with Hearing Loss

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