Face recognition: A literature survey
ACM Computing Surveys (CSUR)
A tutorial on text-independent speaker verification
EURASIP Journal on Applied Signal Processing
Graphical models for text-independent speaker verification
Nonlinear Speech Modeling and Applications
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Speaker classification requires a sufficiently accurate functional description of speaker attributes and the resources used in speaking, to be able to produce new utterances mimicking the speaker's current physical, emotional and cognitive state, with the correct dialect, social class markers and speech habits. We lack adequate functional knowledge of why and how speakers produce the utterances they do, as well as adequate theoretical frameworks embodying the kinds of knowledge, resources and intentions they use. Rhythm and intonation - intimately linked in most language - provide a wealth of information relevant to speaker classification. Functional - as opposed to descriptive - models are needed. Segmental cues to speaker category, and markers for categories like fear, uncertainty, urgency, and confidence are largely un-researched. What Eckman and Friesen did for facial expression must be done for verbal expression. The chapter examines some potentially profitable research possibilities in context.