Hearing Aids and Hearing Impairments Part II

Meena Ramani02/23/05

Discussion Time!

SummarizeFacts on Hearing LossHearing AidsCochlea-IHC and OHCPresbycusis

Decreased AudibilityDecreased Frequency ResolutionDecreased Temporal resolutionDecreased Dynamic Range

Amplification TechniquesLinearCompressive-Single/MultiBand

Room for improvement

Huge Market BTE,ITE,ITC,CIC

OHCs:Sharpen the traveling waveProvide an amplification for soft sounds(40-50 dB SPL)

HL in aging earsOccurs due to damage to OHCs

1) HA has to provide more gain at HFs.2) HAs less gain at LFs Noise Removal

3) Fast acting compression4) Compressive Amplification

Linear-too much gain

Compressive- Overshoots/undershoots

Multiband vs Singleband

Outline Temporal Resolution Frequency Resolution Noise Reduction Techniques Conclusion

Temporal Resolution

What is temporal resolution? What happens to temporal resolution for the

HI? What does poor temporal resolution result in? Implications for HA design

What is temporal resolution?Speech has a lot of temporal information like the presence or absence of acoustic excitation, the periodicity or aperiodicity of excitation _______, ________,______

Speech Envelope Slowly varying Carries Information: Consonants, voicing, phoneme boundaries,

syllable boundaries, stress etc. Lip reading and speech envelope

Modulation Perception Changing the depth of modulation of the envelope Noise and Reverberations

Gap detection threshold Psychoacoustic measure For normals: 2.5ms Relationship between gap detection thresholds and SRTs in noise

(Consonant recognition requires temporal structures)

Temporal resolution for the HI Experimental setup for Modulation Perception:

TMTF- Temporal Modulation Transfer Function Sinusoidal modulation of broadband noise Modulation detection threshold in terms of freq. Comparison with normals: threshold shift /SL

Results : Poor modulation perception is because of reduced listening bandwidth Same behavior at SL inputs for normals and HI

Results for Gap detection measures: Normals: GDT reduces as the frequency of the noise bands increases Same behavior at SL inputs for normals and HI

Signals which are made audible to HI have same temporal resolution as the normals

Temporal resolution for the HI (contd.) Difference in loudness levels

between the envelope maxima and minima is > for impaired ear than normal

This leads one to assume that impaired ear will perceive modulation depth changes better perceptually/Louder

Circles->equal modulation strength.

Contradicts the TMTF results? JND vs Perception Noise also enhanced<Glasberg>

Temporal resolution for the HI (contd.)Effect of Compression on Modulation

Use compression to provide loudness correction.

Fast acting/Syllabic compression 3:1 compression Modulation depth (dB)=20logm AM factor: (1+msin(wmt)) Reduces the modulation depth

by~9.5dB

Implications for HA design

Syllabic compression can compensate for abnormal sensitivity to AM

This compression also improves the discrimination of envelopes having a DR>10dB

But reducing the spectral cues causes in low SNR conditions a low SI.

Frequency Resolution

What is Frequency resolution? What happens to freq. resolution for the HI? What does poor freq. resolution result in? Implications for HA design

What is Frequency resolution?

If change in spectrum of speech causes some change in shape of excitation along basilar membrane=> change exceeds listeners frequency resolutionElse => frequency resolution was not fine enough to discriminate the spectral changes

Frequency resolution for HIStatement: Cochlear damage results in poor freq. resolution

But Auditory filter bandwidth increases with stimulus level…

HOW DO YOU MEASURE FREQ. RESOLUTION?

Experimental setup: Need normals and the HI to be at the same sensation level(SL) Normals: Add broad band background noise to elevate threshold

Results: Freq. resolution measured via tuning curves was worse for HI More Upward spread of masking since LF slope of filter is shallower than for

normals. Conclusion:

Freq. resolution is impaired by both: Damaged auditory system Necessity to listen to high stimulus

What does poor frequency resolution result in?

Loose Spectral Cues Formant peak information is lost Smooths the internal spectral contrasts

Inability to distinguish between vowels F1 & F2 frequencies Important cue for vowel ID

Increase in upper spread of masking CVR-Consonant Vowel Recognition

HI have more problems understanding the speech in noise when compared to normals

Implications for HA design

Fact: For the HI, we have broader auditory filters Sharpen spectral contrast

Narrow the BW of spectral peaks Decrease level of spectral valleys

Not too much success since the broad filters overwhelm the sharpening technique

Multiband/wideband design: Reduction in spectral cues For Multiband correlate AGC in each band

Noise Reduction

HI people have abnormal difficult understanding speech in noise.

Noise Reduction

HI need an SNR of 9dB Broader auditory filters , reduced suppressions Upper spread of masking

SNR improvement doesn’t often correlate with improved SI!

Noise removal algorithms Single-microphone techniques Multi-microphone techniques

Single-microphone techniquesGeneral Considerations Single stream has speech+noise Need to evaluate continuously which frames have

speech and which have noise Improvements in SNR do not relate directly to

improvements in SI Need to evaluate performance of algorithm using

Listening SI tests

Single-microphone techniquesFrequency specific gain reduction BILL-Bass increase at Low Levels

For noise reduction, bass decrease at high levels Reduces LFs when the average gain in that region is high Theoretically should help since the HI LFs mask the HF LF has information about consonant features such as nasality,

voicing etc which was lost Cook et al in 1996 showed that if noise is LF, then HPF the

speech resulted in significant improvement of SI Festen et al in 1990 Envelope minima technique, reduce gain per

band so that envelope minima (noise) is closer to hearing threshold level

Dynamic range based technique: attenuation for noise band inversely proportional to the measured DR

Single-microphone techniquesSpectral subtraction Subtract spectral magnitude of the noise

estimate from the short term spectral magnitude of the signal Assumes stationary noise Uses same phase for the final noise reduced signal SNR improves but SI is same.

Removes noise like cues required for fricatives.

Multiple microphone techniques What is Array Processing? Omni directional microphones: 15mm separation between any two Low frequency roll off of 6dB/octave

Figure 7.15. A typical configuration for a two-microphone (Mic) directional system. The delay to the back microphone determines the angle of the null in the directional pattern.

Figure 7.16. Two directional patterns typically associated with hearing aid directional microphones. The angle represents the direction from which the sound is approaching the listener, with 0 degrees representing directly in front of the listener. The distance from the origin at a given angle represents the gain applied for sound from arriving from that direction, ranging here from 0 to 25dB. The patterns are a cardioid (left) and a hypercardioid (right).

Beamforming

Frequency Dependent

Frequency Independent

Delay and sum

Comparison with noise suppressor

• Noise suppressor (NS) is the standard one used on iDEN phones

Noise Cancellation

Use LMS algorithm Problem is some

speech is fed back to reference mic and gets canceled with noise.

Figure 7.17. A typical two-microphone noise cancellation system. Ideally, the primary microphone measures a mixture of the interfering noise and the target speech, and the reference microphone measures only a transformation of the interfering noise.

Conclusion Parameters selection and fitting is a very difficult

problem Algorithms can make the sound more audible but

not more intelligible IHC have been ignored so far but they could have a

role too. It is difficult to get subjective scores from HI

populations No objective method can account for the non-

linearities introduced by compression Wearable HAs are an option for research but are

inconvenient

Array fundamentals

Speaker tracking is not possible with single microphone

Multiple microphones facilitate spatiotemporal filtering

Setup consists of two microphones with the first microphone assumed as origin

Distance of the wavefront from microphone is

The direction of source is given by

sk dFm

Nc)1(

sin

kd sin