Information Based Speech Transduction

Modern hearing aids use a variety of advanced digital signal processing methods in order to improve speech intelligibility. These methods are based on knowledge about the acoustics outside the ear as well as psychoacoustics. We present a novel observation based on the fact that acoustic prominence is not equal to information prominence for time intervals at the syllabic and sub-syllabic levels. The idea is that speech elements with a high degree of information can be robustly identified based on basic acoustic properties. We evaluated the correlation of (information rich) content words in the DanPASS corpus with fundamental frequency (F0) and spectral tilt across four frequency bands. Our results show a correlation of certain band-level differences and the presence of content words. Similarly, but to a lesser extent, a correlation between F0 and the presence of content words was found. The principle described here has the potential to improve the “information-to-noise” ratio in hearing aids. In addition, this concept may also be applicable in automatic speech recognition systems.