Speech Recognition in Noise for Cochlear Implantees with a Two-Microphone Monaural Adaptive Noise Reduction System

2001 ◽  
Vol 22 (5) ◽  
pp. 420-430 ◽  
Author(s):  
Jan Wouters ◽  
Jeff Vanden Berghe
2005 ◽  
Vol 16 (05) ◽  
pp. 270-277 ◽  
Author(s):  
Todd A. Ricketts ◽  
Benjamin W.Y. Hornsby

This brief report discusses the affect of digital noise reduction (DNR) processing on aided speech recognition and sound quality measures in 14 adults fitted with a commercial hearing aid. Measures of speech recognition and sound quality were obtained in two different speech-in-noise conditions (71 dBA speech, +6 dB SNR and 75 dBA speech, +1 dB SNR). The results revealed that the presence or absence of DNR processing did not impact speech recognition in noise (either positively or negatively). Paired comparisons of sound quality for the same speech in noise signals, however, revealed a strong preference for DNR processing. These data suggest that at least one implementation of DNR processing is capable of providing improved sound quality, for speech in noise, in the absence of improved speech recognition.


2013 ◽  
Vol 11 (1) ◽  
pp. 153-160
Author(s):  
Ivana Ropus ◽  
Vesna Alar ◽  
Biserka Runje

2009 ◽  
Vol 31 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Yunfeng Wu ◽  
Rangaraj M. Rangayyan ◽  
Yachao Zhou ◽  
Sin-Chun Ng

2017 ◽  
Vol 28 (05) ◽  
pp. 415-435 ◽  
Author(s):  
Jace Wolfe ◽  
Mila Duke ◽  
Erin Schafer ◽  
Christine Jones ◽  
Lori Rakita

Background: Children with hearing loss experience significant difficulty understanding speech in noisy and reverberant situations. Adaptive noise management technologies, such as fully adaptive directional microphones and digital noise reduction, have the potential to improve communication in noise for children with hearing aids. However, there are no published studies evaluating the potential benefits children receive from the use of adaptive noise management technologies in simulated real-world environments as well as in daily situations. Purpose: The objective of this study was to compare speech recognition, speech intelligibility ratings (SIRs), and sound preferences of children using hearing aids equipped with and without adaptive noise management technologies. Research Design: A single-group, repeated measures design was used to evaluate performance differences obtained in four simulated environments. In each simulated environment, participants were tested in a basic listening program with minimal noise management features, a manual program designed for that scene, and the hearing instruments’ adaptive operating system that steered hearing instrument parameterization based on the characteristics of the environment. Study Sample: Twelve children with mild to moderately severe sensorineural hearing loss. Data Collection and Analysis: Speech recognition and SIRs were evaluated in three hearing aid programs with and without noise management technologies across two different test sessions and various listening environments. Also, the participants’ perceptual hearing performance in daily real-world listening situations with two of the hearing aid programs was evaluated during a four- to six-week field trial that took place between the two laboratory sessions. Results: On average, the use of adaptive noise management technology improved sentence recognition in noise for speech presented in front of the participant but resulted in a decrement in performance for signals arriving from behind when the participant was facing forward. However, the improvement with adaptive noise management exceeded the decrement obtained when the signal arrived from behind. Most participants reported better subjective SIRs when using adaptive noise management technologies, particularly when the signal of interest arrived from in front of the listener. In addition, most participants reported a preference for the technology with an automatically switching, adaptive directional microphone and adaptive noise reduction in real-world listening situations when compared to conventional, omnidirectional microphone use with minimal noise reduction processing. Conclusions: Use of the adaptive noise management technologies evaluated in this study improves school-age children’s speech recognition in noise for signals arriving from the front. Although a small decrement in speech recognition in noise was observed for signals arriving from behind the listener, most participants reported a preference for use of noise management technology both when the signal arrived from in front and from behind the child. The results of this study suggest that adaptive noise management technologies should be considered for use with school-age children when listening in academic and social situations.


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