Real-time combined compression and linear gain processing for digital hearing aids

Abstract

Amplitude compression processing is used to reduce amplitude-level variations of speech to fit reduced dynamic ranges of hard-of-hearing (HoH) listeners. However, compression processing results in spectral smearing due in part to reduced peak-to-valley ratios. HoH listeners have difficulty detecting important spectral peaks in speech [Nelson and Revoile, 1998]. Thus spectral smearing due to compression processing may have unwanted negative effects on speech understanding. Presented here is a real-time processing algorithm based on a sinusoidal speech model that preserves the important spectral peaks through hybrid compression and linear gain processing. Primary spectral peaks are identified in 7.5-ms analysis frames using 30-ms Hamming windows. A 256-pt FFT is used for speech sampled at 8.013 kHz. The stimuli are divided into frequency bands surrounding the spectral peaks, and the desired compression ratio for each frequency band is applied [Tejero-Calado et al., 1998]. For speech synthesis, an inverse FFT and overlap-add method is used with a triangular window that is double the analysis frame length. The algorithm is currently implemented using a TMS320C30 EVM. The resulting processed speech has good sound quality, compressed amplitude, and preserved spectral contrast. Preliminary tests indicate that HoH listeners benefit from the processing algorithm over conventionally amplified speech signals.