A tutorial on the design and development of automatic speaker-recognition systems is presented. Automatic speaker recognition is the use of a machine to recognize a person from a spoken phrase. These systems can operate in two modes: to identify a particular person or to verify a person's claimed identity. Speech processing and the basic components of automatic speaker-recognition systems are shown and design tradeoffs are discussed. Then, a new automatic speaker-recognition system is given. This recognizer performs with 98.9% correct decalcification. Last, the performances of various systems are compared.

Speaker recognition: a tutorial

Methods are presented for adaptively generating wavelet templates for signal representation and classification using neural networks. Different network structures and energy functions are necessary and are given for representation and classification. The idea is introduced of a "super-wavelet," a linear combination of wavelets that itself is treated as a wavelet. The super-wavelet allows the shape of the wavelet to adapt to a particular problem, which goes beyond adapting parameters of a fixed-shape wavelet. Simulations are given for 1-D signals, with the concepts extendable to imagery. Ideas are discussed for applying the concepts in the paper to phoneme and speaker recognition.

Neural network adaptive wavelets for signal representation and classification

Recent advances in speaker recognition

This chapter overviews recent advances in speaker recognition technology. The first part of the chapter discusses general topics and issues. Speaker recognition can be divided in two ways: (a) speaker identification and verification, and (b) text-dependent and text-independent methods. The second part of the paper is devoted to discussion of more specific topics of recent interest which have led to interesting new approaches and techniques. They include parameter/distance normalization techniques, model adaptation techniques, VQ-/ergodic-HMM-based text-independent recognition methods, and a text-prompted recognition method. The chapter concludes with a short discussion assessing the current status and possibilities for the future.

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An Overview of Speaker Recognition Technology

The task of speaker verification, a subset of the general problem of speaker recognition is defined. The feature selection and pattern matching steps of the recognition procedure are examined. Speaker verification system design and performance are discussed, and databases for evaluating them are briefly considered. An example of a speaker verification system is described. An overview of industry research in this area is given. >

Speaker verification: a tutorial

Text-independent speaker recognition methods have been based on measurements of long-term statistics of individual speech frames. These methods are not capable of modeling speaker-dependent speech dynamics. In this paper, we describe a new method, based on template matching, that utilizes temporal information to advantage. The template-matching method performs text-dependent recognition as a special case. Performance of the template-matching method is compared with that of similar recently-developed methods.

R. Wohlford

Papers

A new method of text-independent speaker recognition