Literature DB >> 24686228

Speech enhancement for listeners with hearing loss based on a model for vowel coding in the auditory midbrain.

Akshay Rao, Laurel H Carney.   

Abstract

A novel signal-processing strategy is proposed to enhance speech for listeners with hearing loss. The strategy focuses on improving vowel perception based on a recent hypothesis for vowel coding in the auditory system. Traditionally, studies of neural vowel encoding have focused on the representation of formants (peaks in vowel spectra) in the discharge patterns of the population of auditory-nerve (AN) fibers. A recent hypothesis focuses instead on vowel encoding in the auditory midbrain, and suggests a robust representation of formants. AN fiber discharge rates are characterized by pitch-related fluctuations having frequency-dependent modulation depths. Fibers tuned to frequencies near formants exhibit weaker pitch-related fluctuations than those tuned to frequencies between formants. Many auditory midbrain neurons show tuning to amplitude modulation frequency in addition to audio frequency. According to the auditory midbrain vowel encoding hypothesis, the response map of a population of midbrain neurons tuned to modulations near voice pitch exhibits minima near formant frequencies, due to the lack of strong pitch-related fluctuations at their inputs. This representation is robust over the range of noise conditions in which speech intelligibility is also robust for normal-hearing listeners. Based on this hypothesis, a vowel-enhancement strategy has been proposed that aims to restore vowel encoding at the level of the auditory midbrain. The signal processing consists of pitch tracking, formant tracking, and formant enhancement. The novel formant-tracking method proposed here estimates the first two formant frequencies by modeling characteristics of the auditory periphery, such as saturated discharge rates of AN fibers and modulation tuning properties of auditory midbrain neurons. The formant enhancement stage aims to restore the representation of formants at the level of the midbrain by increasing the dominance of a single harmonic near each formant and saturating that frequency channel. A MATLAB implementation of the system with low computational complexity was developed. Objective tests of the formant-tracking subsystem on vowels suggest that the method generalizes well over a wide range of speakers and vowels.

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Year:  2014        PMID: 24686228      PMCID: PMC4617199          DOI: 10.1109/TBME.2014.2313618

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  22 in total

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4.  System for automatic formant analysis of voiced speech.

Authors:  R W Schafer; L R Rabiner
Journal:  J Acoust Soc Am       Date:  1970-02       Impact factor: 1.840

5.  Perceptual and physical space of vowel sounds.

Authors:  L C Pols; L J van der Kamp; R Plomp
Journal:  J Acoust Soc Am       Date:  1969-08       Impact factor: 1.840

6.  The acoustics of normal and nasal vowel production.

Authors:  M F Schwartz
Journal:  Cleft Palate J       Date:  1968-04

7.  Contrast enhancement improves the representation of /epsilon/-like vowels in the hearing-impaired auditory nerve.

Authors:  R L Miller; B M Calhoun; E D Young
Journal:  J Acoust Soc Am       Date:  1999-11       Impact factor: 1.840

8.  Revised estimates of human cochlear tuning from otoacoustic and behavioral measurements.

Authors:  Christopher A Shera; John J Guinan; Andrew J Oxenham
Journal:  Proc Natl Acad Sci U S A       Date:  2002-02-26       Impact factor: 11.205

9.  A phenomenological model of the synapse between the inner hair cell and auditory nerve: long-term adaptation with power-law dynamics.

Authors:  Muhammad S A Zilany; Ian C Bruce; Paul C Nelson; Laurel H Carney
Journal:  J Acoust Soc Am       Date:  2009-11       Impact factor: 1.840

10.  Contribution of consonant versus vowel information to sentence intelligibility for young normal-hearing and elderly hearing-impaired listeners.

Authors:  Diane Kewley-Port; T Zachary Burkle; Jae Hee Lee
Journal:  J Acoust Soc Am       Date:  2007-10       Impact factor: 1.840

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  4 in total

1.  Nonlinear auditory models yield new insights into representations of vowels.

Authors:  Laurel H Carney; Joyce M McDonough
Journal:  Atten Percept Psychophys       Date:  2019-05       Impact factor: 2.199

2.  Cues for Diotic and Dichotic Detection of a 500-Hz Tone in Noise Vary with Hearing Loss.

Authors:  Junwen Mao; Kelly-Jo Koch; Karen A Doherty; Laurel H Carney
Journal:  J Assoc Res Otolaryngol       Date:  2015-05-15

3.  Speech Coding in the Midbrain: Effects of Sensorineural Hearing Loss.

Authors:  Laurel H Carney; Duck O Kim; Shigeyuki Kuwada
Journal:  Adv Exp Med Biol       Date:  2016       Impact factor: 2.622

Review 4.  Supra-Threshold Hearing and Fluctuation Profiles: Implications for Sensorineural and Hidden Hearing Loss.

Authors:  Laurel H Carney
Journal:  J Assoc Res Otolaryngol       Date:  2018-05-09
  4 in total

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