Employing heterogeneous information in a multi-stream framework

A multi-stream speech recogniser is based on the combination of multiple feature streams each containing complementary information. In the past, multi-stream research has typically focused on systems that use a single feature extraction method. This heritage from conventional speech recognisers is an unnecessary restriction and both psychoacoustic and phonetic knowledge strongly motivate the use of heterogeneous features. In this paper we investigate how heterogeneous processing can be used in two different multi-stream configurations: first, a system where each stream handles a different frequency region of the speech (a multi-band recogniser) and, second a multi-stream recogniser where each stream handles the full frequency region. For each type of system we compare the performance using both homogeneous and heterogeneous processing. We demonstrate that the use of heterogeneous information significantly improves the clean speech recognition performance motivating us to continue exploring more specifically designed stream processing