2013
DOI: 10.3766/jaaa.24.9.8
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Effects of a Transient Noise Reduction Algorithm on Speech Understanding, Subjective Preference, and Preferred Gain

Abstract: This study demonstrated that the use of the TNR algorithm would not negatively affect speech identification. The results also suggested that this algorithm may improve listening comfort in the presence of transient noise sounds and ensure consistent use of prescribed gain. Such an algorithm may ensure more consistent audibility across listening environments.

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Cited by 12 publications
(22 citation statements)
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“…2,3 Due to these properties transients are not treated appropriately by conventional single-channel noise reduction algorithms, which are designed to reduce stationary or slowly varying noises. 4 A different class of algorithms are beam formers or spatial filtering algorithms. These algorithms do not make assumptions regarding the stationarity of the noise and they are only effective when signal and noise arrive from sufficiently distinct angles (whereby the signal is typically assumed to arrive from the front).…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…2,3 Due to these properties transients are not treated appropriately by conventional single-channel noise reduction algorithms, which are designed to reduce stationary or slowly varying noises. 4 A different class of algorithms are beam formers or spatial filtering algorithms. These algorithms do not make assumptions regarding the stationarity of the noise and they are only effective when signal and noise arrive from sufficiently distinct angles (whereby the signal is typically assumed to arrive from the front).…”
Section: Introductionmentioning
confidence: 99%
“…6,7 Different studies with hearing aid users have yielded somewhat inconclusive outcomes regarding their effectiveness. 4,8-10 …”
Section: Introductionmentioning
confidence: 99%
“…One mechanism has a time constant as short as 10 msec. Another mechanism has an attack time of less than 0.5 msec to provide instantaneous gain reduction in the event of transient sounds (Korhonen et al, 2013). A speech detector feature built into this algorithm differentiates between speech and nonspeech transient sounds based on the rise time of the input signal.…”
Section: Hearing Aids and Fittingmentioning
confidence: 99%
“…The peak sound pressure level of the transient is well above the average sound pressure level. Korhonen et al (2013) reported sound pressure levels and rise times for different recorded transients. The levels varied from 67 dB (A, impulse) for a clicking pen up to 102 dB (A, impulse) for stacking two water glasses.…”
Section: Introductionmentioning
confidence: 99%
“…Hence transient noise reduction (TNR) systems have been developed to reduce the disturbing effects of transient sounds in hearing aids. Several studies have evaluated the efficacy of a TNR in hearing aid users with various transient noises and outcome measures, such as subjective ratings or paired comparisons for speech clarity, annoyance, comfort, loudness and speech perception tests (DiGiovanni, Davlin, and Nagaraj 2011;Keidser et al 2007; Korhonen et al 2013;Liu et al 2012). The results of these studies suggest that TNRs are most effective for loud transients and are not detrimental for speech perception.…”
Section: Introductionmentioning
confidence: 99%