Introduction to Hearing Aids

Moore, Brian C. J.; Popelka, Gerald R.

doi:10.1007/978-3-319-33036-5_1

Cited by 44 publications

(65 citation statements)

References 36 publications

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“…Efforts to discover the biological strategies used by a diversity of species to extract communication signals from noise have potential to uncover evolutionarily novel mechanisms that might be harnessed to improve hearing prosthetics and speech recognition systems. Compared to people with healthy auditory systems, people with hearing loss experience added difficulty communicating in a crowd, and hearing aids and cochlear implants provide limited benefits in such environments [46]. Computer algorithms for automated speech recognition also yield higher error rates in the presence of noise generated by competing speech [47].…”

Section: Discussionmentioning

confidence: 99%

Frogs Exploit Statistical Regularities in Noisy Acoustic Scenes to Solve Cocktail-Party-like Problems

et al. 2017

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SUMMARY Noise is a ubiquitous source of errors in all forms of communication [1]. Noise-induced errors in speech communication, for example, make it difficult for humans to converse in noisy social settings, a challenge aptly named the “cocktail party problem” [2]. Many nonhuman animals also communicate acoustically in noisy social groups, and thus face biologically analogous problems [3]. However, we know little about how the perceptual systems of receivers are evolutionarily adapted to avoid the costs of noise-induced errors in communication. In this study of Cope’s gray treefrog (Hyla chrysoscelis; Hylidae), we investigated whether receivers exploit a potential statistical regularity present in noisy acoustic scenes to reduce errors in signal recognition and discrimination. We developed an anatomical/physiological model of the peripheral auditory system to show that temporal correlation in amplitude fluctuations across the frequency spectrum (“comodulation”) [4–6] is a feature of the noise generated by large breeding choruses of sexually advertising males. In four psychophysical experiments, we investigated whether females exploit comodulation in background noise to mitigate noise-induced errors in evolutionarily critical mate-choice decisions. Subjects experienced fewer errors in recognizing conspecific calls and in selecting the calls of high-quality mates in the presence of simulated chorus noise that was comodulated. These data show unequivocally, and for the first time, that exploiting statistical regularities present in noisy acoustic scenes is an important biological strategy for solving cocktail-party-like problems in nonhuman animal communication.

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Section: Discussionmentioning

confidence: 99%

Frogs Exploit Statistical Regularities in Noisy Acoustic Scenes to Solve Cocktail-Party-like Problems

et al. 2017

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“…The ERB ( f 0 ) is the equivalent rectangular bandwidth ( ERB ) of the Gammachirp auditory filters centered around f 0 (Irino and Patterson 2006 ). The value of ERB is expressed by the following equation (Glasberg and Moore 1990 ; Moore 2012 ; Wang and Brown 2006 ). …”

Section: The Proposed Feature Extraction Based On An Auditory Filter mentioning

confidence: 99%

“…The ERB-rate scale represents an approximately logarithmic function which relates the frequency value to the ERBs number, ERBrate ( f ), and can be expressed by (Glasberg and Moore 1990 ; Moore 2012 ; Wang and Brown 2006 ). …”

Section: The Proposed Feature Extraction Based On An Auditory Filter mentioning

confidence: 99%

“…The second step is the Outer and middle ear filtering, which is performed by a second order low-pass filter with a resonance frequency equal to 4 kHz (Martens and Van Immerseel 1990 ; Van Immerseel and Martens 1992 ). In the third step, the result is processed by applying the gammachirp auditory filterbank composed of 34 Gammachirp filters (Zouhir and Ouni 2013 ), where the centre frequencies of the filter are equally spaced in ERB-rate scale between 50 Hz and 8000 Hz (Glasberg and Moore 1990 ; Moore 2012 ). The output is pre-emphasized, in the fourth step, by the simulated equal loudness curve.…”

Section: The Proposed Feature Extraction Based On An Auditory Filter mentioning

confidence: 99%

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A bio-inspired feature extraction for robust speech recognition

Zouhir

Ouni

2014

SpringerPlus

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In this paper, a feature extraction method for robust speech recognition in noisy environments is proposed. The proposed method is motivated by a biologically inspired auditory model which simulates the outer/middle ear filtering by a low-pass filter and the spectral behaviour of the cochlea by the Gammachirp auditory filterbank (GcFB). The speech recognition performance of our method is tested on speech signals corrupted by real-world noises. The evaluation results show that the proposed method gives better recognition rates compared to the classic techniques such as Perceptual Linear Prediction (PLP), Linear Predictive Coding (LPC), Linear Prediction Cepstral coefficients (LPCC) and Mel Frequency Cepstral Coefficients (MFCC). The used recognition system is based on the Hidden Markov Models with continuous Gaussian Mixture densities (HMM-GM).

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“…It has been assumed that the frequency discrimination by normal-hearing subjects is mainly based on temporal information cues derived from phase locking for frequencies up to 45 kHz [16] whereas above 45 kHz, discrimination is thought to depend on place mechanisms, based on changes in the excitation pattern [2,5]. The supporting arguments come from the behavioral studies [7]. However, some physiological studies by Heinz et al [8,9], Recio-Spinoso et al [10] and Temchin et al [11] suggested the existence of`residual assignment' of neural impulses to always the same phase of the signal (for frequencies above 5 kHz).…”

Section: Introductionmentioning

confidence: 99%

Frequency Discrimination for Amplitude Modulated Sinusoidal Signals at High Carrier Frequencies

Sęk

Kordus

2014

Acta Phys. Pol. A

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The current study is a continuation of experiments presented by S¦k and Bukaªa (Acta Physica Polonica A 123, 1106 (2013). The purpose of the present study was to investigate frequency discrimination of amplitude modulated high frequency carriers. Using 2AFC procedure, the subjects were presented with two observation intervals of which the rst interval contained four pulses of the same high frequency signal (called SSSS), while in the second interval (called SHSH) the second and fourth pulses had higher frequencies values (i.e. shifted upwards by ∆f). The carrier frequency (in S pulses) was xed and equal to 10 kHz. Modulation rates were equal to 100, 200, 337, 500, 600, 733, and 800 Hz. The value of the modulation rate was limited to keep all components of the sinusoidal modulation within one auditory lter (∼ 17% of the center frequency) centered at the carrier frequency. Two dierent types of modulation were used: a simple sinusoidal modulation with the modulation depth m set to 100%, and a logarithmic modulation with the modulation depth m set to 50 dB. Results indicate a strong relationship between frequency discrimination threshold and modulation type. The thresholds are signicantly higher for logarithmic modulation in comparison to sinusoidal modulation. Amplitude modulation as well as logarithmic modulation applied to the high frequency carrier cause signicant increase in the frequency discrimination threshold. For high frequency sinusoidal signal carriers (i.e. close to 10 kHz), frequency discrimination thresholds do not depend on amplitude modulation rates up to about 800 Hz. In general, the excitation pattern mechanism was a primary cue enabling frequency discrimination of modulated and unmodulated signals to compare with the mechanism based on the temporal ne structure. However, the excitation pattern was not the only mechanism responsible for the frequency discrimination.

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Introduction to Hearing Aids

Cited by 44 publications

References 36 publications

Frogs Exploit Statistical Regularities in Noisy Acoustic Scenes to Solve Cocktail-Party-like Problems

Frogs Exploit Statistical Regularities in Noisy Acoustic Scenes to Solve Cocktail-Party-like Problems

A bio-inspired feature extraction for robust speech recognition

Frequency Discrimination for Amplitude Modulated Sinusoidal Signals at High Carrier Frequencies

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