The masking release (i.e., better speech recognition in fluctuating compared to continuous noise backgrounds) observed for normal-hearing (NH) listeners is generally reduced or absent in hearing-impaired (HI) listeners. One explanation for this lies in the effects of reduced audibility: elevated thresholds may prevent HI listeners from taking advantage of signals available to NH listeners during the dips of temporally fluctuating noise where the interference is relatively weak. This hypothesis was addressed through the development of a signal-processing technique designed to increase the audibility of speech during dips in interrupted noise. This technique acts to (i) compare short-term and long-term estimates of energy, (ii) increase the level of short-term segments whose energy is below the average energy, and (iii) normalize the overall energy of the processed signal to be equivalent to that of the original long-term estimate. Evaluations of this energy-equalizing (EEQ) technique included consonant identification and sentence reception in backgrounds of continuous and regularly interrupted noise. For HI listeners, performance was generally similar for processed and unprocessed signals in continuous noise; however, superior performance for EEQ processing was observed in certain regularly interrupted noise backgrounds.

The masking release (MR; i.e., better speech recognition in fluctuating compared with continuous noise backgrounds) that is evident for listeners with normal hearing (NH) is generally reduced or absent for listeners with sensorineural hearing impairment (HI). In this study, a real-time signal-processing technique was developed to improve MR in listeners with HI and offer insight into the mechanisms influencing the size of MR. This technique compares short-term and long-term estimates of energy, increases the level of short-term segments whose energy is below the average energy, and normalizes the overall energy of the processed signal to be equivalent to that of the original long-term estimate. This signal-processing algorithm was used to create two types of energy-equalized (EEQ) signals: EEQ1, which operated on the wideband speech plus noise signal, and EEQ4, which operated independently on each of four bands with equal logarithmic width. Consonant identification was tested in backgrounds of continuous and various types of fluctuating speech-shaped Gaussian noise including those with both regularly and irregularly spaced temporal fluctuations. Listeners with HI achieved similar scores for EEQ and the original (unprocessed) stimuli in continuous-noise backgrounds, while superior performance was obtained for the EEQ signals in fluctuating background noises that had regular temporal gaps but not for those with irregularly spaced fluctuations. Thus, in noise backgrounds with regularly spaced temporal fluctuations, the energy-normalized signals led to larger values of MR and higher intelligibility than obtained with unprocessed signals.

Lou’s early work in the area of improved signal processing for hearing aids included his research on compression amplification to combat the effects of loudness recruitment in listeners with sensorineural hearing loss. Working with his doctoral students (including Rich Lippmann, Steve De Gennaro, and Diane Bustamante), Lou made major contributions towards an analytical understanding of the benefits and limitations of compression amplification as a component of hearing aids. Recently, Lou has been involved in work on a new signal-processing scheme which operates to equalize the energy in a speech signal over time. This energy-equalization (EEQ) scheme shares a similar goal with compression amplification in that they both attempt to match the range of speech levels into the reduced dynamic range of a listener with sensorineural loss. Their operation, however, is different: while compression amplification is based on the actual sound-pressure level of the signal, the EEQ scheme operates on relative energy calculations designed to reduce the variations in overall signal level. In this talk, we will describe the EEQ processing system together with results obtained on its evaluation with hearing-impaired listeners for speech reception in backgrounds of continuous and fluctuating noise.