PERCEPTION OF SPECTRAL RIPPLES & SPEECH IN
NOISE BY GERIATRIC LISTENERS
AUTHORS
Vikas M.D
II MASLP
Department of Audiology and Speech Language Pathology
KMC (A Unit of MANIPAL University), Mangalore-1
ISHA membership no: L -1486
E-mail: vikasmdslp@gmail.com
Hassan P. C.
II MASLP
Department of Audiology and Speech Language Pathology
KMC (A Unit of MANIPAL University), Mangalore-1
ISHA membership no: L-1564
e-mail: hssnpc@gmail.com
Mr. Arivudai Nambi
Assistant Professor in Audiology
Department of Audiology and Speech Language Pathology
KMC (A Unit of MANIPAL University), Mangalore-1
ISHA membership no: L-1009
e-mail: arivudainambi11@gmail.com
Paper Submitted for the 43nd ISHACON
PERCEPTION OF SPECTRAL RIPPLES & SPEECH IN NOISE BY GERIATRIC
LISTENERS
ABSTRACT
INTRODUCTION
Difficulty in understanding speech especially in noise is one of the most frequent
complaints of geriatrics in spite of having normal hearing. This difficulty in speech
perception may be related to poor frequency or temporal resolution. Several
investigators have studied the frequency resolution by estimated auditory filter shape
using notch noise method in geriatrics. They have found that geriatric individuals
have broader auditory filters (Patterson et al., 1928; van Rooji et al. 1982). In
contrast, Sommers and Humes (1993) reported that auditory filter shape in young
and elderly listeners with normal hearing are identical. Recent studies have showed
that broadening of auditory filter is associated with hearing impairment but for normal
hearing individuals the auditory filter shape did not show any differences (Peters and
Moore, 1992).
NEED FOR THE STUDY
There is no clear cut evidence available in literature regarding the spectral resolution
and the speech identification abilities in geriatrics with normal hearing. Hence there
is a need to study the frequency resolution abilities in geriatrics. There are several
methods to measure the frequency resolution like notch noise method,
psychophysical tuning curves. All these procedures have discrete steps, and have to
cover larger frequency range and hence time consuming. However there are simpler
and less time consuming methods like the spectral ripple method to measure the
frequency resolution. In this method complex signal is created with ripples (peaks
and dips) in spectral domain. Ripple density is increased by increasing the no of
ripples per octave. Individual is presented with two stimuli, one with standard
spectrum and other with reverse spectrum. Reverse spectrum will have peaks where
the standard spectrum had dips and vice versa. Ripple discrimination threshold
(RDT) is estimated by measuring highest ripple density at which the individual can
differentiate the ripples with standard & reverse spectrum. Current study assesses
the frequency resolution by estimating the ripple discrimination threshold.
AIM
1. To measure the RDT in geriatrics and young adults.
2. To investigate the speech recognition scores of geriatrics and young adults in
quiet and in the presence of background noise.
3. To correlate the spectral ripple resolution and speech recognition scores in quiet
and in noise.
METHOD
Participants for the study included 15 geriatrics of age range between 45 to 61yrs
(mean age of 53.04yrs) and 15 young adults with the age range of 18yrs to 25yrs
(mean age of 22yrs) with hearing sensitivity within normal limits (within 25dBHL
pure-tone thresholds from 250 to 8000 Hz) and no history of any middle ear
disorders and neurological disorders.
Signal processing
Stimuli with spectral ripples were created in MATLAB 7 environment. Two-hundred
pure-tone frequency components were summed to generate the rippled noise stimuli.
The amplitudes of the components were determined by a full-wave rectified
sinusoidal envelope on a logarithmic amplitude scale. The ripple peaks were spaced
equally on a logarithmic frequency scale. The ripple stimuli were generated with 6
different densities, measured in ripples per octave. The ripple densities differed by
ratios of 1.414 (2.000, 2.828, 4.000, 5.657, 8.000, and 11.314 ripples/octave). For
standard ripples, the phase of the full-wave rectified sinusoidal spectral envelope
was created using ‘sin’ function and for inverted ripples, it was ‘cos’ function.
Four lists of sentences were taken from standardized quick SIN test in
Kannada (Kumar, 2009) in order to assess the speech recognition ability of the
participants. Each list contained 7 sentences and each sentence has 5 key words, so
total of 35 keywords in each list. Speech materials were spoken by male speaker
with Indian English accent. The stimuli were recorded digitally on a data acquisition
system. Four talker babble was added to 3 lists at +10dB, 0dB SNR & -10dB SNR.
List four was presented in quiet.
Procedure
The experiment was performed on a PC equipped with a Creative Labs
SoundBlaster 16 soundcard. The subjects listened to the stimuli via Senheiser stereo
headphones at a comfortable level set by the subjects.
Classical method of constant stimuli with 2AFC task was used to measure
spectral ripple thresholds.10 trails were presented at each ripple density. Subjects
heard two intervals, target interval contained standard & reverse ripples and the
other interval contained either standard & standard or reverse & reverse ripples.
Subject has to identify the target interval by clicking on appropriate button appearing
on screen.
Speech recognition was assessed in open set paradigm for all the four condition
(quiet, +10dBSNR, 0dBSNR & -10dBSNR). Written responses were taken from each
subjects The responses were scored using the ‘loose method’ (Rosen &
Faulkner,1992) in which sentence recognition scores were calculated based on
correctly identified key words.
RESULTS:
To estimate the ripple discrimination threshold (RDT), probability of correct
responses was calculated which followed the weibull distribution. Thresholds were
determined using 75% criteria on weibull psychometric function. Independent t-test
was administered to investigate the effect of age on RDT. Statistical analysis
revealed that young adults performed significantly better (t=-12.031, p<0.05) when
compared to geriatrics.
Speech recognition scores in each condition were calculated by counting the
number of correctly identified key words. Total scores for each condition were
converted into Rationalized Arcsine Unit (RAU) scores to account for the critical
differences that inherently present in conventional scoring method (Studebaker,
1985). These RAU scores were used for further statistical analysis. Independent ‘t’
test revealed that speech identifications were significantly different between young
adults & geriatrics at 0dB (t=-21.795, p<0.05) & -10dB (t=-3.115, p<0.05) scores.
Ceiling was reached for both groups at quiet & +10dB condition. Pearson’s
correlation analysis revealed significant positive correlation between ripple
discrimination threshold and speech recognition scores at 0dBSNR(r=0.88, p<0.05)
and -10dBSNR(r=0.52, p<0.05).
DISCUSSION:
Results of RDT reveals that frequency resolving ability of geriatric individuals is poor
when compared to young adults even though they have normal hearing. This
difference can be attributed the age related changes in cochlear processing
(Patterson et al., 1982) and phase locking (Clinard et.al. 2010). There was no
statistical significant difference observed between two groups for +10dB SNR and no
noise condition as the responses of both the groups reached the ceiling effect.
However, geriatric individual’s had significantly lower speech identification scores at
less favourable SNRs i.e., 0 dB SNR and -10 dB SNR. This difficulty in
understanding speech in noisy situations can be attributed to the poor frequency
resolution as estimated by ripple discrimination threshold. Segregation of target
speech and background noise to separate perceptual streams largely depends on
frequency resolution ability. Good correlation obtained between RDT and speech in
noise also supports the fact that frequency resolution is important to perceive speech
in noise.
CONCLUSION
The current study emphasizes the need to study the frequency resolution ability of a
geriatric individual in order to study the problems faced by the geriatrics especially
during difficult to hear situations. It can be concluded from the current study that poor
speech perception by geriatric individual may also be due to poor frequency
resolution.