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2011 4th International Conference on Biomedical Engineering and Informatics (BMEI)

A Study for the Effect of Widened Auditory Filter of Hearing Impaired Listener

Hongsub An, Euichul Jeong, Youngrok Song Sangbang Choi, Dongseok Jeong, Sangmin Lee

Department of Electronic Engineering Inha University Incheon, Korea

Sangbang Choi, Dongseok Jeong, Sangmin Lee Department of Electronic Engineering

Institute for Information and Electronics Research Inha University Incheon, Korea

Abstract - The reduced frequency selectivity is a typical phenomenon of sensorineural hearing loss. In this paper, we made modeling of reduced frequency selectivity for hearing impaired listener. The model of reduced frequency selectivity was generated with bandwidth control algorithm based on ERB(equivalent rectangular bandwidth) of auditory filter. In other to examine the effectiveness of model, we compared PESQ(perceptual evaluation of speech quality) score and LLR(log likelihood ratio) score with 36 Korean worlds of two syllables. To verify the effect on noise condition, we mixed white and babble noise with 0dB and -3dB SNR to speech words. As the result, PESQ score is lower as extending bandwidth of filter however LLR score is almost same. It means that non-linearity and widen auditory filter characteristics caused by reduced frequency selectivity could be reflected in bandwidth control algorithm.

Keywords-auditory filter; reducedfrequency selectivity; ERB; PESQ; LLR

I. INTRODUCTION People with moderate cochlea hearing loss have difficulty

understanding speech. Researchers have argued that the difficulty in understanding speech arises at least partly from deficits in the ability to discriminate sounds well above the absolute threshold. Such deficits include reduced dynamic range (Villchur, 1974), reduced temporal resolution for fluctuating stimuli (Fitzgibbons and Wightman, 1982; Tyler et al., 1982), reduced ability to discriminate frequency differences in pure and complex tones (Glasberg and Moore, 1989; Moore and Peters, 1992), and reduced frequency selectivity (Pick et al., 1977; Florentine et al., 1984; Glasberg and Moore, 1986; Tyler 1986)[1].

In this study we focus on the effect of reduced frequency selectivity.

II. BACKGROUND

A. Reduced Frequency Selectivity Frequency selectivity is ability to discriminate which is the

higher frequency when heard two different tones. Difference limen(DL) is the smallest change in stimulation that a person could detect and difference limen for frequency(DFL) is to investigate the frequency selectivity. For people with normal hearing frequency can be distinguish even though frequency difference of 0.2 to 0.3 percent in the main dialog area

0.5~2kHz. However conclusions of several studies that measured DLF targeting damaged people to cochlea are observed reduced frequency selectivity. Reduced frequency selectivity is related to the widened auditory filter. Pitch is very important to understand language. However, pitch detect ability is reduced when suffer damage to the cochlea.

Effect of reduced frequency selectivity is described as a comparison of auditory filter shape in normal and impaired people. The auditory filter shape of impaired people is wider than that of normal people such as Figure1 (b) especially in low frequency range[2]. And the distinction of the timbre is well known depends on the frequency selectivity so when damage to the cochlea it is hard to distinguish vowel or musical instrument.

Figure 1. Auditory filter shape of center frequency of 1kHz for the normal (a) and impaired (b) ears.

B. Auditory Filter and ERB Filters are used in many aspects of audiology and

psychoacoustics including the peripheral auditory system. The shape and organisation of the basilar membrane means that different frequencies resonate particularly strongly at different points along the membrance. This leads to a tonotopic organisation[3] of the sensitivity to frequency ranges along the membrane, which can be modeled as being an array of overlapping band-pass filters known as "auditory filters". The auditory filters are associated with points along the basilar membrane and determine the frequency selectivity of the

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cochlea, and therefore the listener’s discrimination between different sounds. They are non-linear, level-dependent and the bandwidth decreases from the base to apex of the cochlea as the tuning on the basilar membrane changes from high to low frequency[4][5].

Another concept associated with the auditory filter is the ERB(Equivalent Rectangular Bandwidth). The ERB shows the relationship between the auditory filter, frequency, and the critical bandwidth.

The auditory filters are assumed to have the form of the roex(p) filter suggested by Patterson et al. (1982):

W(g) = (1 + pg)exp(-pg). (1)

where g is deviation from the center frequency (fc) of the filter divided by fc, W(g) is the intensity weighting function describing the filter shape, and p is a parameter determining the sharpness of the filter. The each bandwidth of auditory filters according to center frequency (fc) are calculated using the equation for the ERB suggested by Glasberg and Moore (1990):

ERB = 24.7(0.00437fc + 1). (2)

where the ERB and fc are both specified in hertz. The Figure 2 shows the auditory filter shape of center

frequency is 1kHz. Figure 2 (a) is the represent symmetric roex filter. As changes the values of pl and pu, filter slope is varied. In symmetric filter pl and pu has same value. Figure 2 (b) is the represent asymmetric roex filter. In this filter pl and pu has different value.

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Figure 2. Auditory filter shape of center frequency of 1kHz : (a) Symmetric roex filter, (b) Asymmetric roex filter.

III. METHOD In this paper shape of auditory filters are modeled using

roex filter in eq (1). And propose to raise the value of ERB for describe the widened auditory filter. Enlarging the value of

ERB, the p parameters of the roex filter be smaller and this expressed widened auditory filter.

Figure 3. The block diagram of algorithm for reflect the characteristics of

auditory filter.

The Figure. 3 is the block diagram of algorithm for reflect the characteristics of auditory filter are discussed in the previous section. In detail, the processing procedure was as follows. Processing was performed on speech signals, low-pass filtered at 7kHz and sampled 16,000 samples per second. Each frame consists of 128 samples. The length of the Hamming window was 128 samples corresponding to an input frame size. The windowed signal were padded with 64 zeros on each side and converted to the frequency domain with a 256-point FFT. The converted signal was separated into power and phase components. Before processing, the 256-by-256 point matrices representing the auditory filters were calculated through Eq. (1) and Eq. (2). To calculate a frame of waveform samples, the smeared power components were obtained by multiply power components by matrix and phase components were recombined, and a 256-point inverse FFT was implemented. Finally using the overlap-add algorithm, four frames contributed to each 64-point segment of the output waveform.

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Figure 4. The power sepctrum graph of original speech signals and were passed auditory filters, ERB X 1, ERB X 2, ERB X 3.

Figure 4 shows a Korean sentence “안녕하세요(hello)” from the top to bottom the original signal, ERB X 1, ERB X 3 and ERB X 6 respectively, and ERB X 1, ERB X 3, ERB X 6

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are shown in the spectrum of the output sound after through the auditory filter. The graph of original signal and the ERB X 1 are almost same. However the original signal compared with the ERB X 3 and ERB X 6 due to the effects of widened auditory filters the pitch characteristics disappearance of the voice signal.

IV. RESULT

A. PESQ Result The figure5 shows average PESQ score of 36 Korean

words of two syllables. The noise situations are absence noise, -0dB SNR and -3dB SNR. Each word was mixed noise and passed auditory filters, ERB X 3 and ERB X6. Figure5 (a) is white and (b) is babble noise.

The average PESQ score of ERB X 3 is higher than ERB X 6 in all noise situations that means speech quality is decreased as extend of filter bandwidth.

Figure 5. PESQ experiment result for the white (a) and babble (b) noise

B. LLR Result The figure6 shows average LLR score of 36 Korean words

of two syllables. The noise situations are absence noise, -0dB SNR and -3dB SNR. Each word was mixed noise and passed auditory filters, ERB X 3 and ERB X6. Figure5 (a) is white and (b) is babble noise.

The average LLR scores of ERB X 3 and ERB X 6 are almost same. Despite the difference in PESQ score, almost same score of LLR means that both non-linearity and widened auditory filter characteristics caused by reduced frequency selectivity could be reflected in bandwidth control algorithm.

Figure 6. LLR experiment result for the white (a) and babble (b) noise

V. CONCLUSION The PESQ is measurement to reflect the perceptual of the

human hearing. And LLR is measurement to assess the linear distortion. In the PESQ experiments, as the auditory filter bandwidth is wider as the score is higher. However in the LLR experiments, the score is almost same although there are differences in the bandwidth of the filter because non-linearity auditory characteristics of human. This result means that both non-linearity and widened auditory filter characteristics caused by reduced frequency selectivity could be reflected in bandwidth control algorithm.

ACKNOWLEDGMENT This work was supported by Key Research Institute

Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education, Science and Technology(2011-0018394). And this work was supported by the MKE(The Ministry of Knowledge Economy), Korea, under the CITRC(Convergence Information Technology Research Center) support program (NIPA-2011-C6150-1102-0001) supervised by the NIPA(National IT Industry Promotion Agency)

REFERENCES [1] Brian C. J. Moore and Brian R. Glasberg, "Simulation of the effects of

loudness recruitment and threshold elevation on the intelligibility of speech in quiet and in a background of speech," Acoustical Society of america., vol, 94, no. 4, 1993, pp. 2050-2062.

[2] Glasberg, B.R., and Brian C. J. Moore, "Auditory filter shapes in subjects with unliateral and bilateral cochlea impairments”. Acoust Society of America., vol. 79, no. 4, pp. 1020-33, 1986.

[3] R. Munkong, B.-H. Juang, "Auditory perception and cognition", IEEE Signal Processing Magazine, vol. 25, no. 3, pp. 98-117, 2008.

[4] Gelfand, S. A. "Hearing: an introduction to psychological and physiological acoustics", (4th ed.). New York, Marcel Dekker, ISBN 0-585-26606-9, 2004.

[5] Moore, B. C. J. "Cochlear hearing loss", London, Whurr Publishers Ltd, ISBN 0-585-12256-3, 1998