C HAPTER N INE Introduction The sophistication of hearing aid (HA) signal pro- cessing has increased rapidly in the last decade. Several specific advancements have been developed with the goal of mitigating the negative perceptual and psycho- logical consequences of background noise for HA users. While attempts to reduce unwanted noise for HA users have been made over the last three decades (see Bentler and Chiou 2006 for a review), modern digital noise re- duction (DNR) algorithms attempt to limit background noise by initially classifying the input to the HA based on the acoustic characteristics of the listening environ- ment. When noise is the primary signal detected by the HA, DNR algorithms reduce gain to improve listener comfort. Ideally, DNR should maintain audibility for the speech signal if speech and noise are both present in the environment. The sophistication of current DNR algo- rithms allows for these changes to be made independ- ently across multiple frequency bands simultaneously. Optimization across frequency bands minimizes distor- tion of the speech signal by only providing DNR in the frequency bands where noise dominates the input signal (Hoetink , Korossy and Dreschler 2009). Although these goals may sound simple in theory, overlap between the frequency spectra of speech and noise in realistic envi- ronments (Koopman, Franck and Dreschler 2001) has the potential to limit the algorithm from achieving these goals. Specifically, the expected improvements in the signal-to-noise ratio (SNR) and speech perception in noise may not be realized outside of laborator y settings. Because DNR has been made a standard feature available in most digital hearing aids within the last decade, scrutiny regarding the efficacy and appropriate- ness of such algorithms for children who wear hearing aids has surfaced. Studies of DNR with adult listeners have begun to illustrate the potential advantages of DNR in terms of listener comfort in noise, showing that im- proved comfort can be achieved without negatively im- pacting speech understanding. Unfortunately, research evaluating the efficacy of DNR for pediatric hearing aid users has been limited. Lack of substantive evidence to support the use of DNR with children has led to recom- mendations that DNR be implemented with caution (Palmer and Grimes 2005). Clinicians must determine if DNR should be activated for their pediatric hearing aid clients despite limited evidence to support their decision to use this widely available feature. If an audiologist de- termines that DNR may be appropriate for a given child, it is important that the effects of the processing on the speech signal be included in the verification process. Just as verification is important for other advanced sig- nal processing strategies, it is necessary with DNR so any potential changes in the speech signal be identified and optimal settings obtained. The purpose of this article is to provide a brief re- view of how DNR is implemented in HAs. Previous stud- ies with adult listeners are highlighted in addition to a more detailed discussion regarding outcomes of the lim- ited number of recent DNR studies completed with chil- dren. A practical verification procedure for clinicians to evaluate DNR with their pediatric clients is presented. Strategies for optimizing DNR algorithms to minimize the impact on speech audibility are discussed, as well as 153 Should Digital Noise Reduction be Activated in Pediatric Hearing Aid Fittings? Ryan W. McCreery, Samantha Gustafson and Patricia G. Stelmachowicz Address correspondence to: Ryan W. McCreery, M.S., CCC-A, Boys Town National Research Hospital, 555 North 30th Street, Omaha, NE 68131, Email: ryan.mccreery@boystown.org.