Detection of unknown speakers in an unsupervised speech controlled system

Abstract

In this paper we investigate the capability of our self-learning speech controlled system comprising speech recognition, speaker identification and speaker adaptation to detect unknown users. Our goal is to enhance automated speech controlled systems by an unsupervised personalization of the human-computer interface. New users should be allowed to use a speech controlled device without the need to identify themselves or to undergo a time-consumptive enrollment. Instead, the system should detect new users during the operation of the device. New speaker profiles should be initialized and incrementally adjusted without any additional intervention of the user. Such a personalization of human-computer interfaces represents an important research issue. Exemplarily, in-car applications such as speech controlled navigation, hands-free telephony or infotainment systems are investigated. Results for detecting unknown speakers are presented for a subset of the SPEECON database. © 2010 Springer-Verlag.