Papers about Speaker recognition

The current practice in virtual human dialogue systems is to use professional human recordings or limited-domain speech synthesis. Both approaches lead to good performance but at a high cost. To determine the best trade-off between performance and cost, we perform a systematic evaluation of human and synthesized voices with regard to naturalness, conversational aspect, and likability. We also vary the type (in-domain vs. out-of-domain), length, and content of utterances, and take into account the age... Read more

In this article we present a research scheme which aims to analyze the use of Embodied Conversational Agent (ECA) technology to improve the robustness and acceptability of speaker enrolment and verification dialogues designed to provide secure access through natural and intuitive speaker recognition. In order to find out the possible effects of the visual information channel provided by the ECA, tests were carried out in which users were divided into two groups, each interacting with... Read more

One of the biggest obstacles for constructing effective sociable virtual humans lies in the failure of machines to recognize the desires, feelings and intentions of the human user. Virtual humans lack the ability to fully understand and decode the communication signals human users emit when communicating with each other. This article describes our research in overcoming this problem by developing senses for the virtual humans which enables them to hear and understand human speech,... Read more

In this paper we survey the state of the art in direct and indirect human computer interaction based biometrics. Direct HCI biometrics are based on abilities, style, preference, knowledge, or strategy used by people while working with a computer. The indirect HCI-based biometrics are events that can be obtained by monitoring users’ HCI behavior indirectly via observable low-level actions of computer software. We examine current research and analyze the types of features used to describe... Read more

ELIZA is a program operating within the MAC time-sharing system at MIT which makes certain kinds of natural language conversation between man and computer possible. Input sentences are analyzed on the basis of decomposition rules which are triggered by key words appearing in the input text. Responses are generated by reassembly rules associated with selected decomposition rules. The fundamental technical problems with which ELIZA is concerned are: (1) the identification of key words, (2) the... Read more