Effects of Noise and Noise Suppression on Speech Perception by Cochlear Implant Users

Hochberg, Irving; Boothroyd, Arthur; Weiss, Mark R.; Hellman, Sharon A.

doi:10.1097/00003446-199208000-00008

Cited by 83 publications

(67 citation statements)

References 11 publications

(14 reference statements)

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“…If the noise reduction algorithm could accurately estimate the noise spectrum, the within-channel SNR is improved in the processed signal. Several research groups have implemented the spectral subtraction noise reduction algorithm and reported improved speech recognition scores for CI users ͑Weiss, 1993; Hochberg et al, 1992;Goldsworthy, 2005͒.…”

Section: Discussionmentioning

confidence: 99%

“…For example, the Audallion BEAMformer that summed the inputs from two directional microphones worn in the implanted ear and in the contralateral ear was reported to have limited benefit on localizing the source of sounds ͑Figueiredo et al, 2001͒, limited directional effects ͑Goldsworthy, 2005͒, and limited acceptability among CI users. In addition, several groups of researchers have reported positive findings using spectral subtraction noise reduction algorithms to enhance the speech recognition of CI users in background noise ͑Hochberg et al, 1992;Weiss, 1993;Goldsworthy, 2005͒. The computational demand, however, prevents such algorithms from being implemented in wearable CIs.…”

Section: Introductionmentioning

confidence: 99%

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Effects of directional microphone and adaptive multichannel noise reduction algorithm on cochlear implant performance

Chung¹,

Zeng²,

Acker³

2006

The Journal of the Acoustical Society of America

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Although cochlear implant ͑CI͒ users have enjoyed good speech recognition in quiet, they still have difficulties understanding speech in noise. We conducted three experiments to determine whether a directional microphone and an adaptive multichannel noise reduction algorithm could enhance CI performance in noise and whether Speech Transmission Index ͑STI͒ can be used to predict CI performance in various acoustic and signal processing conditions. In Experiment I, CI users listened to speech in noise processed by 4 hearing aid settings: omni-directional microphone, omni-directional microphone plus noise reduction, directional microphone, and directional microphone plus noise reduction. The directional microphone significantly improved speech recognition in noise. Both directional microphone and noise reduction algorithm improved overall preference. In Experiment II, normal hearing individuals listened to the recorded speech produced by 4-or 8-channel CI simulations. The 8-channel simulation yielded similar speech recognition results as in Experiment I, whereas the 4-channel simulation produced no significant difference among the 4 settings. In Experiment III, we examined the relationship between STIs and speech recognition. The results suggested that STI could predict actual and simulated CI speech intelligibility with acoustic degradation and the directional microphone, but not the noise reduction algorithm. Implications for intelligibility enhancement are discussed.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Effects of directional microphone and adaptive multichannel noise reduction algorithm on cochlear implant performance

Chung¹,

Zeng²,

Acker³

2006

The Journal of the Acoustical Society of America

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“…However, when listening conditions are less favorable, implant users may encounter much greater difficulty than their normal-hearing counterparts. For example, even small amounts of background noise can cause implant listeners to experience substantial reductions in speech recognition (Fu, Shannon, & Wang, 1998;Hochberg, Boothroyd, Weiss, & Hellman, 1992).…”

Section: Discussionmentioning

confidence: 99%

Effects of Presentation Level on Phoneme and Sentence Recognition in Quiet by Cochlear Implant Listeners

Donaldson

Allen

2003

Ear and Hearing

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Objective: The objectives of this study were to characterize the effects of presentation level on speech recognition in quiet by cochlear implant users with the Nucleus 22 SPEAK and Clarion v1.2 CIS speechprocessing strategies, and to relate speech recognition at low presentation levels to stimulus audibility as measured by sound field thresholds. It was hypothesized that speech recognition performance in both Nucleus SPEAK and Clarion CIS participants would decrease as presentation level was decreased below 50 to 60 dBA, due to audibility limitations. However, it was expected that such level effects would be less severe in CIS participants than in SPEAK participants because the Clarion v1.2 device encodes a wider acoustic dynamic range (up to 60 dB) than the Nucleus 22 device (30 dB).Design: Performance-intensity (P-I) functions for vowels, consonants and sentences in quiet were obtained from each participant. P-I functions incorporated speech levels of 70, 60, 50, 40 and 30 dBA. Subjects used their clinical speech processor maps and adjusted the loudness (volume/sensitivity) controls on their processors so that speech presented at 60 dBA was comfortably loud. Maps were created using default clinical procedures and were not adjusted to optimize sound field thresholds. Sound field thresholds and dynamic ranges were measured for warbled pure tones with frequencies of 250 to 6000 Hz.Results: Consonant and sentence recognition showed strong level effects for both SPEAK and CIS participants, with performance decreasing substantially at levels below 50 dBA in most individuals. Vowel recognition showed weaker level effects. For all three speech materials, SPEAK and CIS participants demonstrated similar mean performance at 70 dBA; however, SPEAK participants showed larger reductions in performance than CIS participants with decreasing level. Sound field thresholds were more sensitive for CIS participants than for SPEAK participants, supporting the hypothesis that performance differences were related to audibility. Conclusions:Cochlear implant listeners are unable to maintain good speech recognition at low presentation levels due to reduced stimulus audibility, and this may significantly limit their ability to communicate in daily life. It is likely that audibility differences between SPEAK and CIS participants in the present study can be attributed at least partly to differences in the acoustic dynamic range used by the respective processors. However, several additional factors may have contributed to differences in audibility and perception of soft speech among individual listeners with both devices. These include the minimum and maximum electrical stimulation levels specified in participants' maps and the speech processor sensitivity setting used for testing.

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“…However, speech performance deteriorates rapidly with increased levels of background noise, even for the best CI users. Understanding CI users' susceptibility to noise remains a major challenge for researchers (e.g., Dowell et al 1987;Hochberg et al 1992;Kiefer et al 1996;Mü llerDeiler et al 1995;Skinner et al 1994), and is an important step toward improving CI users' performance in noisy listening conditions. Recent innovations in electrode design and speech processing have helped to improve CI users' performance in noise (Skinner et al 1994;Kiefer et al 1996).…”

Section: Introductionmentioning

confidence: 99%

Noise Susceptibility of Cochlear Implant Users: The Role of Spectral Resolution and Smearing

Nogaki

2005

JARO

339

298

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The latest-generation cochlear implant devices provide many deaf patients with good speech recognition in quiet listening conditions. However, speech recognition deteriorates rapidly as the level of background noise increases. Previous studies have shown that, for cochlear implant users, the absence of fine spectro-temporal cues may contribute to poorer performance in noise, especially when the noise is dynamic (e.g., competing speaker or modulated noise). Here we report on sentence recognition by cochlear implant users and by normal-hearing subjects listening to an acoustic simulation of a cochlear implant, in the presence of steady or square-wave modulated speech-shaped noise. Implant users were tested using their everyday, clinically assigned speech processors. In the acoustic simulation, normal-hearing listeners were tested for different degrees of spectral resolution (16, eight, or four channels) and spectral smearing (carrier filter slopes of j24 or j6 dB/octave). For modulated noise, normal-hearing listeners experienced significant release from masking when the original, unprocessed speech was presented (which preserved the spectrotemporal fine structure), while cochlear implant users experienced no release from masking. As the spectral resolution was reduced, normal-hearing listeners' release from masking gradually diminished. Release from masking was further reduced as the degree of spectral smearing increased. Interestingly, the mean speech recognition thresholds of implant users were very close to those of normal-hearing subjects listening to four-channel spectrally smeared noise-band speech. Also, the best cochlear implant listeners performed like normal-hearing subjects listening to eight-to 16-channel spectrally smeared noise-band speech. These findings suggest that implant users' susceptibility to noise may be caused by the reduced spectral resolution and the high degree of spectral smearing associated with channel interaction. Efforts to improve the effective number of spectral channels as well as reduce channel interactions may improve implant performance in noise, especially for temporally modulated noise.

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Effects of Noise and Noise Suppression on Speech Perception by Cochlear Implant Users

Cited by 83 publications

References 11 publications

Effects of directional microphone and adaptive multichannel noise reduction algorithm on cochlear implant performance

Effects of directional microphone and adaptive multichannel noise reduction algorithm on cochlear implant performance

Effects of Presentation Level on Phoneme and Sentence Recognition in Quiet by Cochlear Implant Listeners

Noise Susceptibility of Cochlear Implant Users: The Role of Spectral Resolution and Smearing

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