Comparison of a Hearing Aid Fitting Formula Based on Korean Acoustic Characteristics and Existing Fitting Formulae

Jin, In-Ki; Lee, Kyungwon; Kim, Jinsook; Kim, Dong-Wook; Sohn, Jeong-Ho; Lee, Junghak

doi:10.21848/asr.2017.13.3.216

Cited by 6 publications

(5 citation statements)

References 10 publications

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“…As various characteristics of HA significantly affect listeners’ performance, all subjects applied for a HA with the same conditions designed for the research purpose and developed by Samsung Electronics-namely, behind-the-ear style, 8 channels, and vent-occluded. Then, Hallym Audiology Institute-version 1 developed by Jin, et al [ 17 ] for Korean language specific HA fitting formula was applied and was also individually adjusted except for CT and/or RT variables.…”

Section: Methodsmentioning

confidence: 99%

Preferred Compression Threshold and Release Time in Quiet and Noisy Conditions for Elderly Korean Hearing Aid Users

et al. 2017

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Background and ObjectivesListeners with sensorineural hearing loss want to compensate for their narrow dynamic range from appropriate compression functions of hearing aids. The present study aimed to determine which compression threshold and release time of nonlinear hearing aids might affect speech recognition and speech quality judgments.Subjects and MethodsTen elderly listeners with symmetrical moderate-to-severe sensorineural hearing loss participated in the study. To compare two compression threshold (31 dB SPL vs. 61 dB SPL) and two release time (50 ms vs. 500 ms) conditions, subjects’ speech recognition was measured using the Korean version of the Hearing in Noise Test in both quiet and noisy situations. All subjects were also asked to rate the degree of speech quality in terms of loudness, sharpness, clarity, and background noise immediately after completing the speech recognition test.ResultsAlthough no significant difference emerged in speech recognition thresholds between the two compression thresholds in the quiet situation, the compression threshold of 31 dB SPL showed a lower (or better) signal-to-noise ratio of speech recognition compared to that of 61 dB SPL. The release times of 50 and 500 ms did not statistically differ in both quiet and noisy situations. Subjective categories were found to be louder and clearer in the 50 ms release time for quiet and noisy, respectively.ConclusionsWe expect that these patterns of current results will apply for better-fitting protocol of elderly Korean hearing aid users.

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Section: Methodsmentioning

confidence: 99%

Preferred Compression Threshold and Release Time in Quiet and Noisy Conditions for Elderly Korean Hearing Aid Users

et al. 2017

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“…This procedure uses the desired sensation levels to measure the empirical real-ear-aided gain [ 3 ]. Although these fitting formulas differ in their underlying principles, restoring the individual's audibility is the main concern for all of them, which is primarily based on the English language [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

“…is procedure uses the desired sensation levels to measure the empirical real-ear-aided gain [3]. Although these tting formulas di er in their underlying principles, restoring the individual's audibility is the main concern for all of them, which is primarily based on the English language [8]. It has been acknowledged that up to 50% of hearing aid users prefer amplification or compression settings different from those recommended by the manufacturer [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, Sandlin et al [1] examined the advantages of hearing aid personalization by considering different facts in a smartphone-based system. e dynamic range (DR), the long-term average speech spectrum (LTASS), and the band importance function (BIF) of speech are the most substantial features of language in terms of acoustics and linguistic attributes [8]. erefore, these characteristics should be considered to restore audibility in individuals with hearing loss by measuring the degree of amplification required across the frequency bands [16].…”

Section: Introductionmentioning

confidence: 99%

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Machine Learning-Based Hearing Aid Fitting Personalization Using Clinical Fitting Data

Mondol

Kim

et al. 2022

Journal of Healthcare Engineering

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The initial software fitting prescribed by the fitting formula largely depends on the patient’s hearing loss, which may not be the optimal preference for a particular user. Certain criteria must also be readjusted by an audiologist to meet the user-specific requirements. Therefore, this study focuses on the novel application of a neural network (NN) technique to build a suitable fitting algorithm with prescribed hearing loss and the corresponding preferred gain to minimize the gap between optimized fittings. The algorithm intended to learn the hearing preferences of an individual user such that the initial fitting may be optimized. These findings demonstrate the efficiency of the algorithm, with and without additional features. Using the clinical fitting data, the average mean square error (MSE) for the simple NN algorithm was 5.4183%. By adding additional features to the data, the algorithm performed better, and the average MSE was as low as 5.2530%. However, the algorithm outperformed Company A fitting software, as the MSE was the highest at 5.4748%. As the company’s automatic fitting has a noticeable discrepancy with clinical fitting records, the impeccable results from this study can lead to a better path towards fitting satisfaction, thus benefiting the hearing-impaired community to a larger extent.

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“…It is also known that acoustic and linguistic characteristics of a language have a bearing on LTASS and DR. Thus, the SII [5,6] as well as optimal gain and compression required for hearing aids can be language dependent [7][8][9]. Unfortunately, not many studies have been conducted to estimate LTASS and DR for Indian languages, which are spoken by over1.3 billion people.…”

Section: Introductionmentioning

confidence: 99%

Cross-language comparison of long-term average speech spectrum and dynamic range for three Indian languages and British English

Narne¹,

Tiwari²

2021

Clin Arch Commun Disord

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Purpose: The Long-Term Average Speech Spectrum (LTASS) and Dynamic Range (DR) of speech strongly influence estimates of Speech Intelligibility Index (SII), gain and compression required for hearing aid fitting. It is also known that acoustic and linguistic characteristics of a language have a bearing on its LTASS and DR. Thus, there is a need to estimate LTASS and DR for Indian languages. The present work on three Indian languages fills this gap and contrasts LTASS and DR attributes of these languages against British English.Methods: For this purpose, LTASS and DR were measured for 21 one-third octave bands in the frequency range of 0.1 to 10 kHz for Hindi, Kannada, Indian English and British English.Results: Our work shows that the DR of Indian languages studied is 7-10 dB less relative to that of British English. We also report that LTASS levels for Indian languages are 7 dB lower relative to British English for frequencies above 1 kHz. Finally, we observed that LTASS and DR attributes across genders were more or less the same.Conclusions: Given the evidence presented in this work that LTASS and DR characteristics for Indian languages analyzed are markedly different than those for BE, there is a need to determine Indian language specific SII, as well as gain and compression parameters used in hearing aids.

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Comparison of a Hearing Aid Fitting Formula Based on Korean Acoustic Characteristics and Existing Fitting Formulae

Cited by 6 publications

References 10 publications

Preferred Compression Threshold and Release Time in Quiet and Noisy Conditions for Elderly Korean Hearing Aid Users

Preferred Compression Threshold and Release Time in Quiet and Noisy Conditions for Elderly Korean Hearing Aid Users

Machine Learning-Based Hearing Aid Fitting Personalization Using Clinical Fitting Data

Cross-language comparison of long-term average speech spectrum and dynamic range for three Indian languages and British English

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