Evaluation of a noise‐reduction algorithm that targets non‐speech transient sounds

dously in their acoustic characteristics, such as spectral and temporal properties, loudness, pitch, timing, rhythm, and timbre. While some sounds are pleasant to listen to and desirable to hear, other sounds are loud or may be outright annoying to listen to. The categorization of sounds is, of course, very individual, and not necessarily related to the sound’s acoustic characteristics.1 A recent study found that when using an 11-point rating scale, with 0 labeled “not annoying at all” and 10 labeled “very annoying,” the mean annoyance rating of everyday noises by hearing aid users varied from 4.9 for soft transient sounds (e.g., computer key strokes) to 7.4 for loud stationary sounds (e.g., a vacuum cleaner). 2 The standard deviation value, however, was much greater for soft transient sounds (4.1) than for other sounds (1.1 – 2.5), suggesting that a wide range of sounds—from soft to loud and from transient to stationary—were rated as relatively annoying by the study participants. While it is impossible to predict which sounds will cause discomfort to any given individual, it is certain that negative reactions to sounds can harm our well-being, both psychologically and physiologically.3 Therefore, problems with noise should not be overlooked. Although the average annoyance rating that aided hearing-impaired listeners assign to some common everyday noises do not appear to differ from the ratings given by normal-hearing listeners,4 hearing aid users often complain about listening in noise.5,6 There are even data that show that successful hearing aid use is related to the individual’s tolerance for background noise.7,8 Therefore, it would seem that ensuring that users are not unnecessarily bothered by unwanted sounds should be an important objective in hearing aid design. Common features used in hearing aids to minimize the negative effects of noise include compression9 and noise reduction.10 Typically, digital noise-reduction algorithms are modulation-based in order to distinguish noise from speech, and compression is used in conjunction with time constants that are long enough to ensure that the temporal characteristics of speech are not distorted. This means that both these approaches for making noises more comfortable to listen to are most effective for continuous stationary noises. Clinical anecdotes and the study by Hernandez et al. suggest, however, that short transient sounds, such as a door slamming or clattering cutlery, can also cause discomfort or annoyance to the hearing aid user.2 Traditional signal processing strategies appear to do little to relieve the annoyance caused by these sounds. One manufacturer has now taken a step designed to fill in this gap. Recently, Siemens introduced a noise-management system in its high-end device that includes a noise-reduction algorithm targeted at non-speech transient sounds. In brief, the algorithm uses the steepness of the envelope slope of the incoming sound to determine if the sound is speech or noise. If the envelope slopes are steeper than are typical for speech, gain is reduced.11 This processing scheme acts very quickly in the time domain and independently in different frequency bands. We conducted a study at the National Acoustic Laboratories (NAL) to evaluate the effectiveness of the new algorithm.