Πέμπτη 14 Ιανουαρίου 2016
Description of Adults Seeking Hearing Help for the First Time According to Two Health Behavior Change Approaches: Transtheoretical Model (Stages of Change) and Health Belief Model.
Objectives: Several models of health behavior change are commonly used in health psychology. This study applied the constructs delineated by two models-the transtheoretical model (in which readiness for health behavior change can be described with the stages of precontemplation, contemplation and action) and the health belief model (in which susceptibility, severity, benefits, barriers, self-efficacy, and cues to action are thought to determine likelihood of health behavior change)-to adults seeking hearing help for the first time. Design: One hundred eighty-two participants (mean age: 69.5 years) were recruited following an initial hearing assessment by an audiologist. Participants' mean four-frequency pure-tone average was 35.4 dB HL, with 25.8% having no hearing impairment, 50.5% having a slight impairment, and 23.1% having a moderate or severe impairment using the World Health Organization definition of hearing loss. Participants' hearing-related attitudes and beliefs toward hearing health behaviors were examined using the University of Rhode Island Change Assessment (URICA) and the health beliefs questionnaire (HBQ), which assess the constructs of the transtheoretical model and the health belief model, respectively. Participants also provided demographic information, and completed the hearing handicap inventory (HHI) to assess participation restrictions, and the psychosocial impact of hearing loss (PIHL) to assess the extent to which hearing impacts competence, self-esteem, and adaptability. Results: Degree of hearing impairment was associated with participation restrictions, perceived competence, self-esteem and adaptability, and attitudes and beliefs measured by the URICA and the HBQ. As degree of impairment increased, participation restrictions measured by the HHI, and impacts of hearing loss, as measured by the PIHL, increased. The majority of first-time help seekers in this study were in the action stage of change. Furthermore, relative to individuals with less hearing impairment, individuals with more hearing impairment were at more advanced stages of change as measured by the URICA (i.e., higher contemplation and action scores relative to their precontemplation score), and they perceived fewer barriers and more susceptibility, severity, benefits and cues to action as measured by the HBQ. Multiple regression analyses showed participation restrictions (HHI scores) to be a highly significant predictor of stages of change explaining 30% to 37% of the variance, as were duration of hearing difficulty, and perceived benefits, severity, self-efficacy and cues to action assessed by the HBQ. Conclusions: The main predictors of stages of change in first-time help seekers were reported participation restrictions and duration of hearing difficulty, with constructs from the health belief model also explaining some of the variance in stages of change scores. The transtheoretical model and the health belief model are valuable for understanding hearing health behaviors and can be applied when developing interventions to promote help seeking. Copyright (C) 2016 Wolters Kluwer Health, Inc. All rights reserved.
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Description of Adults Seeking Hearing Help for the First Time According to Two Health Behavior Change Approaches: Transtheoretical Model (Stages of Change) and Health Belief Model.
Objectives: Several models of health behavior change are commonly used in health psychology. This study applied the constructs delineated by two models-the transtheoretical model (in which readiness for health behavior change can be described with the stages of precontemplation, contemplation and action) and the health belief model (in which susceptibility, severity, benefits, barriers, self-efficacy, and cues to action are thought to determine likelihood of health behavior change)-to adults seeking hearing help for the first time. Design: One hundred eighty-two participants (mean age: 69.5 years) were recruited following an initial hearing assessment by an audiologist. Participants' mean four-frequency pure-tone average was 35.4 dB HL, with 25.8% having no hearing impairment, 50.5% having a slight impairment, and 23.1% having a moderate or severe impairment using the World Health Organization definition of hearing loss. Participants' hearing-related attitudes and beliefs toward hearing health behaviors were examined using the University of Rhode Island Change Assessment (URICA) and the health beliefs questionnaire (HBQ), which assess the constructs of the transtheoretical model and the health belief model, respectively. Participants also provided demographic information, and completed the hearing handicap inventory (HHI) to assess participation restrictions, and the psychosocial impact of hearing loss (PIHL) to assess the extent to which hearing impacts competence, self-esteem, and adaptability. Results: Degree of hearing impairment was associated with participation restrictions, perceived competence, self-esteem and adaptability, and attitudes and beliefs measured by the URICA and the HBQ. As degree of impairment increased, participation restrictions measured by the HHI, and impacts of hearing loss, as measured by the PIHL, increased. The majority of first-time help seekers in this study were in the action stage of change. Furthermore, relative to individuals with less hearing impairment, individuals with more hearing impairment were at more advanced stages of change as measured by the URICA (i.e., higher contemplation and action scores relative to their precontemplation score), and they perceived fewer barriers and more susceptibility, severity, benefits and cues to action as measured by the HBQ. Multiple regression analyses showed participation restrictions (HHI scores) to be a highly significant predictor of stages of change explaining 30% to 37% of the variance, as were duration of hearing difficulty, and perceived benefits, severity, self-efficacy and cues to action assessed by the HBQ. Conclusions: The main predictors of stages of change in first-time help seekers were reported participation restrictions and duration of hearing difficulty, with constructs from the health belief model also explaining some of the variance in stages of change scores. The transtheoretical model and the health belief model are valuable for understanding hearing health behaviors and can be applied when developing interventions to promote help seeking. Copyright (C) 2016 Wolters Kluwer Health, Inc. All rights reserved.
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Description of Adults Seeking Hearing Help for the First Time According to Two Health Behavior Change Approaches: Transtheoretical Model (Stages of Change) and Health Belief Model.
Objectives: Several models of health behavior change are commonly used in health psychology. This study applied the constructs delineated by two models-the transtheoretical model (in which readiness for health behavior change can be described with the stages of precontemplation, contemplation and action) and the health belief model (in which susceptibility, severity, benefits, barriers, self-efficacy, and cues to action are thought to determine likelihood of health behavior change)-to adults seeking hearing help for the first time. Design: One hundred eighty-two participants (mean age: 69.5 years) were recruited following an initial hearing assessment by an audiologist. Participants' mean four-frequency pure-tone average was 35.4 dB HL, with 25.8% having no hearing impairment, 50.5% having a slight impairment, and 23.1% having a moderate or severe impairment using the World Health Organization definition of hearing loss. Participants' hearing-related attitudes and beliefs toward hearing health behaviors were examined using the University of Rhode Island Change Assessment (URICA) and the health beliefs questionnaire (HBQ), which assess the constructs of the transtheoretical model and the health belief model, respectively. Participants also provided demographic information, and completed the hearing handicap inventory (HHI) to assess participation restrictions, and the psychosocial impact of hearing loss (PIHL) to assess the extent to which hearing impacts competence, self-esteem, and adaptability. Results: Degree of hearing impairment was associated with participation restrictions, perceived competence, self-esteem and adaptability, and attitudes and beliefs measured by the URICA and the HBQ. As degree of impairment increased, participation restrictions measured by the HHI, and impacts of hearing loss, as measured by the PIHL, increased. The majority of first-time help seekers in this study were in the action stage of change. Furthermore, relative to individuals with less hearing impairment, individuals with more hearing impairment were at more advanced stages of change as measured by the URICA (i.e., higher contemplation and action scores relative to their precontemplation score), and they perceived fewer barriers and more susceptibility, severity, benefits and cues to action as measured by the HBQ. Multiple regression analyses showed participation restrictions (HHI scores) to be a highly significant predictor of stages of change explaining 30% to 37% of the variance, as were duration of hearing difficulty, and perceived benefits, severity, self-efficacy and cues to action assessed by the HBQ. Conclusions: The main predictors of stages of change in first-time help seekers were reported participation restrictions and duration of hearing difficulty, with constructs from the health belief model also explaining some of the variance in stages of change scores. The transtheoretical model and the health belief model are valuable for understanding hearing health behaviors and can be applied when developing interventions to promote help seeking. Copyright (C) 2016 Wolters Kluwer Health, Inc. All rights reserved.
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Mandarin speech-in-noise and tone recognition using vocoder simulations of the temporal limits encoder for cochlear implants
Temporal envelope-based signal processing strategies are widely used in cochlear-implant(CI) systems. It is well recognized that the inability to convey temporal fine structure (TFS) in the stimuli limits CI users' performance, but it is still unclear how to effectively deliver the TFS. A strategy known as the temporal limits encoder (TLE), which employs an approach to derive the amplitude modulator to generate the stimuli coded in an interleaved-sampling strategy, has recently been proposed. The TLE modulator contains information related to the original temporal envelope and a slow-varying TFS from the band signal. In this paper, theoretical analyses are presented to demonstrate the superiority of TLE compared with two existing strategies, the clinically available continuous-interleaved-sampling (CIS) strategy and the experimental harmonic-single-sideband-encoder strategy. Perceptual experiments with vocoder simulations in normal-hearing listeners are conducted to compare the performance of TLE and CIS on two tasks (i.e., Mandarin speech reception in babble noise and tone recognition in quiet). The performance of the TLE modulator is mostly better than (for most tone-band vocoders) or comparable to (for noise-band vocoders) the CIS modulator on both tasks. This work implies that there is some potential for improving the representation of TFS with CIs by using a TLE strategy.
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Vocal imitations of basic auditory features
Describing complex sounds with words is a difficult task. In fact, previous studies have shown that vocal imitations of sounds are more effective than verbal descriptions [Lemaitre and Rocchesso (2014). J. Acoust. Soc. Am. 135, 862–873]. The current study investigated how vocal imitations of sounds enable their recognition by studying how two expert and two lay participants reproduced four basic auditory features: pitch,tempo, sharpness, and onset. It used 4 sets of 16 referent sounds (modulated narrowband noises and pure tones), based on 1 feature or crossing 2 of the 4 features. Dissimilarity rating experiments and multidimensional scalinganalyses confirmed that listeners could accurately perceive the four features composing the four sets of referent sounds. The four participants recorded vocal imitations of the four sets of sounds. Analyses identified three strategies: (1) Vocal imitations of pitch and temporeproduced faithfully the absolute value of the feature; (2) Vocal imitations of sharpness transposed the feature into the participants' registers; (3) Vocal imitations of onsets categorized the continuum of onset values into two discrete morphological profiles. Overall, these results highlight that vocal imitations do not simply mimic the referent sounds, but seek to emphasize the characteristic features of the referent sounds within the constraints of human vocal production.
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A Neural-Based Vocoder Implementation for Evaluating Cochlear Implant Coding Strategies
Publication date: Available online 14 January 2016
Source:Hearing Research
Author(s): Nawal El Boghdady, Andrea Kegel, Wai Kong Lai, Norbert Dillier
Most simulations of cochlear implant (CI) coding strategies rely on standard vocoders that are based on purely signal processing techniques. However, these models neither account for various biophysical phenomena, such as neural stochasticity and refractoriness, nor for effects of electrical stimulation, such as spectral smearing as a function of stimulus intensity. In this paper, a neural model that accounts for stochastic firing, parasitic spread of excitation across neuron populations, and neuronal refractoriness, was developed and augmented as a preprocessing stage for a standard 22-channel noise-band vocoder. This model was used to subjectively and objectively assess consonant discrimination in commercial and experimental coding strategies.Stimuli consisting of consonant-vowel (CV) and vowel-consonant-vowel (VCV) tokens were processed by either the Advanced Combination Encoder (ACE) or the Excitability Controlled Coding (ECC) strategies, and later resynthesized to audio using the aforementioned vocoder model. Baseline performance was measured using unprocessed versions of the speech tokens.Behavioural responses were collected from seven normal hearing (NH) volunteers, while EEG data were recorded from five NH participants. Psychophysical results indicate that while there may be a difference in consonant perception between the two tested coding strategies, mismatch negativity (MMN) waveforms do not show any marked trends in CV or VCV contrast discrimination.
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Source:Hearing Research
Author(s): Nawal El Boghdady, Andrea Kegel, Wai Kong Lai, Norbert Dillier
Most simulations of cochlear implant (CI) coding strategies rely on standard vocoders that are based on purely signal processing techniques. However, these models neither account for various biophysical phenomena, such as neural stochasticity and refractoriness, nor for effects of electrical stimulation, such as spectral smearing as a function of stimulus intensity. In this paper, a neural model that accounts for stochastic firing, parasitic spread of excitation across neuron populations, and neuronal refractoriness, was developed and augmented as a preprocessing stage for a standard 22-channel noise-band vocoder. This model was used to subjectively and objectively assess consonant discrimination in commercial and experimental coding strategies.Stimuli consisting of consonant-vowel (CV) and vowel-consonant-vowel (VCV) tokens were processed by either the Advanced Combination Encoder (ACE) or the Excitability Controlled Coding (ECC) strategies, and later resynthesized to audio using the aforementioned vocoder model. Baseline performance was measured using unprocessed versions of the speech tokens.Behavioural responses were collected from seven normal hearing (NH) volunteers, while EEG data were recorded from five NH participants. Psychophysical results indicate that while there may be a difference in consonant perception between the two tested coding strategies, mismatch negativity (MMN) waveforms do not show any marked trends in CV or VCV contrast discrimination.
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A Neural-Based Vocoder Implementation for Evaluating Cochlear Implant Coding Strategies
Publication date: Available online 14 January 2016
Source:Hearing Research
Author(s): Nawal El Boghdady, Andrea Kegel, Wai Kong Lai, Norbert Dillier
Most simulations of cochlear implant (CI) coding strategies rely on standard vocoders that are based on purely signal processing techniques. However, these models neither account for various biophysical phenomena, such as neural stochasticity and refractoriness, nor for effects of electrical stimulation, such as spectral smearing as a function of stimulus intensity. In this paper, a neural model that accounts for stochastic firing, parasitic spread of excitation across neuron populations, and neuronal refractoriness, was developed and augmented as a preprocessing stage for a standard 22-channel noise-band vocoder. This model was used to subjectively and objectively assess consonant discrimination in commercial and experimental coding strategies.Stimuli consisting of consonant-vowel (CV) and vowel-consonant-vowel (VCV) tokens were processed by either the Advanced Combination Encoder (ACE) or the Excitability Controlled Coding (ECC) strategies, and later resynthesized to audio using the aforementioned vocoder model. Baseline performance was measured using unprocessed versions of the speech tokens.Behavioural responses were collected from seven normal hearing (NH) volunteers, while EEG data were recorded from five NH participants. Psychophysical results indicate that while there may be a difference in consonant perception between the two tested coding strategies, mismatch negativity (MMN) waveforms do not show any marked trends in CV or VCV contrast discrimination.
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Source:Hearing Research
Author(s): Nawal El Boghdady, Andrea Kegel, Wai Kong Lai, Norbert Dillier
Most simulations of cochlear implant (CI) coding strategies rely on standard vocoders that are based on purely signal processing techniques. However, these models neither account for various biophysical phenomena, such as neural stochasticity and refractoriness, nor for effects of electrical stimulation, such as spectral smearing as a function of stimulus intensity. In this paper, a neural model that accounts for stochastic firing, parasitic spread of excitation across neuron populations, and neuronal refractoriness, was developed and augmented as a preprocessing stage for a standard 22-channel noise-band vocoder. This model was used to subjectively and objectively assess consonant discrimination in commercial and experimental coding strategies.Stimuli consisting of consonant-vowel (CV) and vowel-consonant-vowel (VCV) tokens were processed by either the Advanced Combination Encoder (ACE) or the Excitability Controlled Coding (ECC) strategies, and later resynthesized to audio using the aforementioned vocoder model. Baseline performance was measured using unprocessed versions of the speech tokens.Behavioural responses were collected from seven normal hearing (NH) volunteers, while EEG data were recorded from five NH participants. Psychophysical results indicate that while there may be a difference in consonant perception between the two tested coding strategies, mismatch negativity (MMN) waveforms do not show any marked trends in CV or VCV contrast discrimination.
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A Neural-Based Vocoder Implementation for Evaluating Cochlear Implant Coding Strategies
Publication date: Available online 14 January 2016
Source:Hearing Research
Author(s): Nawal El Boghdady, Andrea Kegel, Wai Kong Lai, Norbert Dillier
Most simulations of cochlear implant (CI) coding strategies rely on standard vocoders that are based on purely signal processing techniques. However, these models neither account for various biophysical phenomena, such as neural stochasticity and refractoriness, nor for effects of electrical stimulation, such as spectral smearing as a function of stimulus intensity. In this paper, a neural model that accounts for stochastic firing, parasitic spread of excitation across neuron populations, and neuronal refractoriness, was developed and augmented as a preprocessing stage for a standard 22-channel noise-band vocoder. This model was used to subjectively and objectively assess consonant discrimination in commercial and experimental coding strategies.Stimuli consisting of consonant-vowel (CV) and vowel-consonant-vowel (VCV) tokens were processed by either the Advanced Combination Encoder (ACE) or the Excitability Controlled Coding (ECC) strategies, and later resynthesized to audio using the aforementioned vocoder model. Baseline performance was measured using unprocessed versions of the speech tokens.Behavioural responses were collected from seven normal hearing (NH) volunteers, while EEG data were recorded from five NH participants. Psychophysical results indicate that while there may be a difference in consonant perception between the two tested coding strategies, mismatch negativity (MMN) waveforms do not show any marked trends in CV or VCV contrast discrimination.
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Source:Hearing Research
Author(s): Nawal El Boghdady, Andrea Kegel, Wai Kong Lai, Norbert Dillier
Most simulations of cochlear implant (CI) coding strategies rely on standard vocoders that are based on purely signal processing techniques. However, these models neither account for various biophysical phenomena, such as neural stochasticity and refractoriness, nor for effects of electrical stimulation, such as spectral smearing as a function of stimulus intensity. In this paper, a neural model that accounts for stochastic firing, parasitic spread of excitation across neuron populations, and neuronal refractoriness, was developed and augmented as a preprocessing stage for a standard 22-channel noise-band vocoder. This model was used to subjectively and objectively assess consonant discrimination in commercial and experimental coding strategies.Stimuli consisting of consonant-vowel (CV) and vowel-consonant-vowel (VCV) tokens were processed by either the Advanced Combination Encoder (ACE) or the Excitability Controlled Coding (ECC) strategies, and later resynthesized to audio using the aforementioned vocoder model. Baseline performance was measured using unprocessed versions of the speech tokens.Behavioural responses were collected from seven normal hearing (NH) volunteers, while EEG data were recorded from five NH participants. Psychophysical results indicate that while there may be a difference in consonant perception between the two tested coding strategies, mismatch negativity (MMN) waveforms do not show any marked trends in CV or VCV contrast discrimination.
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A Neural-Based Vocoder Implementation for Evaluating Cochlear Implant Coding Strategies
Publication date: Available online 14 January 2016
Source:Hearing Research
Author(s): Nawal El Boghdady, Andrea Kegel, Wai Kong Lai, Norbert Dillier
Most simulations of cochlear implant (CI) coding strategies rely on standard vocoders that are based on purely signal processing techniques. However, these models neither account for various biophysical phenomena, such as neural stochasticity and refractoriness, nor for effects of electrical stimulation, such as spectral smearing as a function of stimulus intensity. In this paper, a neural model that accounts for stochastic firing, parasitic spread of excitation across neuron populations, and neuronal refractoriness, was developed and augmented as a preprocessing stage for a standard 22-channel noise-band vocoder. This model was used to subjectively and objectively assess consonant discrimination in commercial and experimental coding strategies.Stimuli consisting of consonant-vowel (CV) and vowel-consonant-vowel (VCV) tokens were processed by either the Advanced Combination Encoder (ACE) or the Excitability Controlled Coding (ECC) strategies, and later resynthesized to audio using the aforementioned vocoder model. Baseline performance was measured using unprocessed versions of the speech tokens.Behavioural responses were collected from seven normal hearing (NH) volunteers, while EEG data were recorded from five NH participants. Psychophysical results indicate that while there may be a difference in consonant perception between the two tested coding strategies, mismatch negativity (MMN) waveforms do not show any marked trends in CV or VCV contrast discrimination.
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Source:Hearing Research
Author(s): Nawal El Boghdady, Andrea Kegel, Wai Kong Lai, Norbert Dillier
Most simulations of cochlear implant (CI) coding strategies rely on standard vocoders that are based on purely signal processing techniques. However, these models neither account for various biophysical phenomena, such as neural stochasticity and refractoriness, nor for effects of electrical stimulation, such as spectral smearing as a function of stimulus intensity. In this paper, a neural model that accounts for stochastic firing, parasitic spread of excitation across neuron populations, and neuronal refractoriness, was developed and augmented as a preprocessing stage for a standard 22-channel noise-band vocoder. This model was used to subjectively and objectively assess consonant discrimination in commercial and experimental coding strategies.Stimuli consisting of consonant-vowel (CV) and vowel-consonant-vowel (VCV) tokens were processed by either the Advanced Combination Encoder (ACE) or the Excitability Controlled Coding (ECC) strategies, and later resynthesized to audio using the aforementioned vocoder model. Baseline performance was measured using unprocessed versions of the speech tokens.Behavioural responses were collected from seven normal hearing (NH) volunteers, while EEG data were recorded from five NH participants. Psychophysical results indicate that while there may be a difference in consonant perception between the two tested coding strategies, mismatch negativity (MMN) waveforms do not show any marked trends in CV or VCV contrast discrimination.
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A Neural-Based Vocoder Implementation for Evaluating Cochlear Implant Coding Strategies
Publication date: Available online 14 January 2016
Source:Hearing Research
Author(s): Nawal El Boghdady, Andrea Kegel, Wai Kong Lai, Norbert Dillier
Most simulations of cochlear implant (CI) coding strategies rely on standard vocoders that are based on purely signal processing techniques. However, these models neither account for various biophysical phenomena, such as neural stochasticity and refractoriness, nor for effects of electrical stimulation, such as spectral smearing as a function of stimulus intensity. In this paper, a neural model that accounts for stochastic firing, parasitic spread of excitation across neuron populations, and neuronal refractoriness, was developed and augmented as a preprocessing stage for a standard 22-channel noise-band vocoder. This model was used to subjectively and objectively assess consonant discrimination in commercial and experimental coding strategies.Stimuli consisting of consonant-vowel (CV) and vowel-consonant-vowel (VCV) tokens were processed by either the Advanced Combination Encoder (ACE) or the Excitability Controlled Coding (ECC) strategies, and later resynthesized to audio using the aforementioned vocoder model. Baseline performance was measured using unprocessed versions of the speech tokens.Behavioural responses were collected from seven normal hearing (NH) volunteers, while EEG data were recorded from five NH participants. Psychophysical results indicate that while there may be a difference in consonant perception between the two tested coding strategies, mismatch negativity (MMN) waveforms do not show any marked trends in CV or VCV contrast discrimination.
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Source:Hearing Research
Author(s): Nawal El Boghdady, Andrea Kegel, Wai Kong Lai, Norbert Dillier
Most simulations of cochlear implant (CI) coding strategies rely on standard vocoders that are based on purely signal processing techniques. However, these models neither account for various biophysical phenomena, such as neural stochasticity and refractoriness, nor for effects of electrical stimulation, such as spectral smearing as a function of stimulus intensity. In this paper, a neural model that accounts for stochastic firing, parasitic spread of excitation across neuron populations, and neuronal refractoriness, was developed and augmented as a preprocessing stage for a standard 22-channel noise-band vocoder. This model was used to subjectively and objectively assess consonant discrimination in commercial and experimental coding strategies.Stimuli consisting of consonant-vowel (CV) and vowel-consonant-vowel (VCV) tokens were processed by either the Advanced Combination Encoder (ACE) or the Excitability Controlled Coding (ECC) strategies, and later resynthesized to audio using the aforementioned vocoder model. Baseline performance was measured using unprocessed versions of the speech tokens.Behavioural responses were collected from seven normal hearing (NH) volunteers, while EEG data were recorded from five NH participants. Psychophysical results indicate that while there may be a difference in consonant perception between the two tested coding strategies, mismatch negativity (MMN) waveforms do not show any marked trends in CV or VCV contrast discrimination.
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