Simultaneous speech recognition and speaker identification

In this paper we present a self-learning speech controlled system comprising speech recognition, speaker identification and speaker adaptation for a small number of users, e.g. five recurring speakers. A compact representation of speech and speaker characteristics is discussed. It is combined with a technique for efficient information retrieval to capture individual speech characteristics allowing robust speaker identification with limited training data. Speech recognition is enhanced by applying speaker specific profiles which are incrementally adapted. However, the computational load and memory consumption are essential design parameters for an embedded system. Such a personalization of human-computer interfaces represents an important research issue. In this paper in-car applications such as speech controlled navigation, hands-free telephony or infotainment systems are investigated. Results for a subset of the SPEECON database are presented. They validate the benefit of the unified modeling of speech and speaker characteristics.