Recent concepts and challenges in hearing research

In everyday life, the speech we listen to is often mixed with many other sound sources as well as reverberation. In such a situation, normal-hearing listeners are able to effortlessly segregate a single voice out of the background, which is commonly known as the 'cocktail party effect'. Conversely, hearing-impaired people have great difficulty understanding speech when more than one person is talking, even when reduced audibility has been fully compensated for by a hearing aid. As with the hearing impaired, the performance of automatic speech recognition systems deteriorates dramatically with additional sound sources. The reasons for these difficulties are not well understood. Only by obtaining a clearer understanding of the auditory system’s coding strategies will it be possible to design intelligent compensation algorithms for hearing devices. This presentation highlights recent concepts of the signal processing strategies employed by the normal as well as impaired auditory system. The aim is to develop a computational auditory signal-processing model, capable of describing the transformation from the acoustical input signal into its “internal (neural) representations”. Several stages of processing are considered to be important for a robust signal representation and a deficiency in any of these processing stages is likely to result in a deterioration of the entire system’s performance. A state-of-the-art model of auditory signal processing would be of major practical significance for technical applications, in digital hearing aids, cochlear implants, speech and audio coding, and automatic speech recognition.