1 New Technique for Improving Speech Intelligibility for the Hearing Impaired Miriam Furst-Yust...

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1 New Technique for Improving Speech Intelligibility for the Hearing Impaired Miriam Furst-Yust Miriam Furst-Yust School of Electrical Engineering School of Electrical Engineering Tel Aviv University Tel Aviv University
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Page 1: 1 New Technique for Improving Speech Intelligibility for the Hearing Impaired Miriam Furst-Yust School of Electrical Engineering Tel Aviv University.

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New Technique for Improving Speech Intelligibility for the Hearing

Impaired

Miriam Furst-YustMiriam Furst-Yust

School of Electrical EngineeringSchool of Electrical Engineering

Tel Aviv UniversityTel Aviv University

Page 2: 1 New Technique for Improving Speech Intelligibility for the Hearing Impaired Miriam Furst-Yust School of Electrical Engineering Tel Aviv University.

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The Hearing Aid ProblemThe Hearing Aid Problem Current hearing aids are very helpful to severe and profound Current hearing aids are very helpful to severe and profound

hearing impairment in quiet environment. hearing impairment in quiet environment.

Most people with mild-to-moderate hearing loss are unable to understand speech in a noisy background.

Current Hearing aids are useless in a noisy background.

Page 3: 1 New Technique for Improving Speech Intelligibility for the Hearing Impaired Miriam Furst-Yust School of Electrical Engineering Tel Aviv University.

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THE PROBLEM:THE PROBLEM:

common noise suppression common noise suppression techniques are not robust and techniques are not robust and

most of the time are not most of the time are not effectiveeffective

Page 4: 1 New Technique for Improving Speech Intelligibility for the Hearing Impaired Miriam Furst-Yust School of Electrical Engineering Tel Aviv University.

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Our ApproachOur Approach

A single microphone followed by a A single microphone followed by a cochlear model algorithm that improves cochlear model algorithm that improves the signal-to-noise ratio.the signal-to-noise ratio.

The algorithm is robust, so speech with The algorithm is robust, so speech with high SNRs are not distorted. high SNRs are not distorted.

Page 5: 1 New Technique for Improving Speech Intelligibility for the Hearing Impaired Miriam Furst-Yust School of Electrical Engineering Tel Aviv University.

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Cochlear Representation Cochlear Representation AlgorithmAlgorithm

A Device that Mimicsthe Human Hearing

and Speech Perception

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Mimic the cochlear representation of Mimic the cochlear representation of speech signalsspeech signals

Identify the speech areas in the Identify the speech areas in the cochlear representation and discard the cochlear representation and discard the noise areasnoise areas

Reconstruct the speech signal from the Reconstruct the speech signal from the modified cochlear representationmodified cochlear representation

Cochlear Representation Algorithm (CRA)

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Cochlear RepresentationsCochlear Representations of of TonesTones

Cochlear representation

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Representation of a wordRepresentation of a word

Input Signal: The word “SHEN”

INPUT OUTPUT

NormalEar

Damaged Ear

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SpectrogramTime representation

Input SpeechInput Speech

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Energy Estimation Energy Mask

Energy Estimation

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TIME (sec)

Cochlear Representation

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Modified Cochlear Representation

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Time representation Spectrogram

Speech Reconstruction

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CRACRA Performance Performance

MELPMELP

2.42.4 Kb/sKb/sG729G729

88 Kb/sKb/s

MELPMELP

2.42.4 Kb/sKb/sG729G729

88 Kb/sKb/s

Noisy Sentence Clean Sentence

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Analysis of Human Analysis of Human Performances with CRA:Performances with CRA: Recognition of CVC words in an Recognition of CVC words in an

open setopen setSubjects: Subjects:

1.1. Hearing Impaired with their Cochlear Hearing Impaired with their Cochlear ImplantsImplants

2.2. Hearing Impaired with their Hearing Hearing Impaired with their Hearing Aids Aids

3.3. Normal HearingNormal Hearing

Page 16: 1 New Technique for Improving Speech Intelligibility for the Hearing Impaired Miriam Furst-Yust School of Electrical Engineering Tel Aviv University.

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Word database - HABWord database - HAB

HHebrew adaptation (Kishon-Rabin,2002) to AB ebrew adaptation (Kishon-Rabin,2002) to AB ((AArthur rthur BBoothroyd) list (Boothroyd,1968) oothroyd) list (Boothroyd,1968) comprising CVC words.comprising CVC words.

Equal distributions in each list of phonemes in the Equal distributions in each list of phonemes in the Hebrew languageHebrew language

HAB common use in hearing tests. Reduces effect HAB common use in hearing tests. Reduces effect of frequency and/or familiarity on test scoresof frequency and/or familiarity on test scores

Two speakers: male and female. 15 lists of 10 Two speakers: male and female. 15 lists of 10 words (total of 300 words)words (total of 300 words)

Recorded at a sampling rate of 44.1 kHzRecorded at a sampling rate of 44.1 kHz

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Applied Word databaseApplied Word database

Test subject’s ability to recognize words in Test subject’s ability to recognize words in noisy environmentsnoisy environments

Gaussian white noise in SNRs of 0 – 30 dBGaussian white noise in SNRs of 0 – 30 dB Bandpass filter 500-8000 HzBandpass filter 500-8000 Hz Apply cochlear model and reconstruction Apply cochlear model and reconstruction

algorithmalgorithm

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Normal Hearing PerformancesNormal Hearing Performancesin open-set words identificationin open-set words identification

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Hearing Aid Users Hearing Aid Users PerformancesPerformances

in open-set words identificationin open-set words identification

Signal-to-Noise Ratio (dB)

0

10

20

30

40

50

60

70

No Noise 30 24 18

Hearing Aid

HearingAid+CRA

Perc

en

tag

e

Corr

ect

)%(

* Hearing Impaired performance were significantly improved by CRA in SNR of 18 dB

No. of Subjects=51

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Cochlear Implant Users Cochlear Implant Users PerformancesPerformances

in open-set words identificationin open-set words identification

Signal-to-Noise Ratio (dB)

0

10

20

30

40

50

60

No Noise 30 24 18

Hearing Aid

HearingAid+CRA

Perc

en

tag

e

Corr

ect

)%(

* Hearing Impaired performance were significantly improved by CRA in SNR of 18, 24 and 30 dB

No. of Subjects=16

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Why CRA is Beneficial to the Why CRA is Beneficial to the Hearing Impaired Hearing Impaired

but Not Effective but Not Effective

to Normal Hearing Subjects?to Normal Hearing Subjects?

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Normal Hearing Recognition Normal Hearing Recognition rate of 2.5 Oct. Band Limited rate of 2.5 Oct. Band Limited

SpeechSpeech

0102030405060708090

100

Clean SNR=0 dB SNR=3 dB

600 Hz

2500 Hz

No filter

Center Frequency = 600 Hz

Center Frequency = 2500 Hz

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Summary & Conclusions: Summary & Conclusions: Normal Hearing PeopleNormal Hearing People

Speech is redundant in the frequency Speech is redundant in the frequency domain.domain.

Normal Hearing subjects can efficiently Normal Hearing subjects can efficiently recognize speech in noisy environments recognize speech in noisy environments because they identify the speech in because they identify the speech in different frequency bands.different frequency bands.

CRA reduces the speech redundancy.CRA reduces the speech redundancy. Therefore, CRA that is applied to a wide-Therefore, CRA that is applied to a wide-

band signal is not effective to normal band signal is not effective to normal hearing people. hearing people.

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Summary & Conclusions: Summary & Conclusions: Hearing Impaired People Hearing Impaired People

Hearing Impaired people have band Hearing Impaired people have band limited hearing.limited hearing.

The speech redundancy is not very The speech redundancy is not very useful to the hearing impaired.useful to the hearing impaired.

Therefore, CRA can be very effective Therefore, CRA can be very effective to the hearing impaired. to the hearing impaired.

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Hardware Solution :Real time Implementation of the

Algorithm

Implementation of the algorithm as Implementation of the algorithm as part of common digital hearing aid or part of common digital hearing aid or Cochlear Implant. Cochlear Implant.

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Real Time ImplementationReal Time Implementation