Publications
Robust text-independent speaker identification using Gaussian mixture speaker models
Summary
Summary
This paper introduces and motivates the use of Gaussian mixture models (GMM) for robust text-independent speaker identification. The individual Gaussian components of a GMM are shown to represent some general speaker-dependent spectral shapes that are effective for modeling speaker identify. The focus of this work is on applications which require...
Speaker identification and verification using Gaussian mixture speaker models
Summary
Summary
This paper presents high performance speaker identification and verification systems based on Gaussian mixture speaker models: robust, statistically based representations of speaker identification. The identification system is a maximum likelihood classifier and the verification system is a likelihood ratio hypothesis tester using background speaker normalization. The systems are evaluated on...
Energy onset times for speaker identification
Summary
Summary
Onset times of resonant energy pulses are measured with the high-resolution Teager operator and used as features in the Reynolds Gaussian-mixture speaker identification algorithm. Feature sets are constructed with primary pitch and secondary pulse locations derived from low and high speech formants. Preliminary testing was performed with a confusable 40-speaker...
Formant AM-FM for speaker identification
Summary
Summary
The performance of systems for speaker identification (SID) can be quite good with clean speech, though much lower with degraded speech. Thus it is useful to search for new features for SID, particularly features that are robust over a degraded channel. This paper investigates features that are robust over a...
Experimental evaluation of features for robust speaker identification
Summary
Summary
This correspondence presents an experimental evaluation of different features and channel compensation techniques for robust speaker identification. The goal is to keep all processing and classification steps constant and to vary only the features and compensations used to allow a controlled comparison. A general, maximum-likelihood classifier based on Gaussian mixture...
Large population speaker recognition using wideband and telephone speech
Summary
Summary
The two largest factors affecting automatic speaker identification performance are the size of the population to be distinguished among and the degradations introduced by noisy communication channels (e.g. telephone transmission). To experimentally examine these two factors, this paper presents text-independent speaker identification results for varying speaker population sizes up to...
Integrated models of signal and background with application to speaker identification in noise
Summary
Summary
This paper is concerned with the problem of robust parametric model estimation and classification in noisy acoustic environments. Characterization and modeling of the external noise sources in these environments is in itself an important issue in noise compensation. The techniques described here provide a mechanism for integrating parametric models of...
An integrated speech-background model for robust speaker identification
Summary
Summary
This paper examines a procedure for text independent speaker identification in noisy environments where the interfering background signals cannot be characterized using traditional broadband or impulsive noise models. In the procedure, both the speaker and the background processes are modeled using mixtures of Gaussians. Speaker and background models are integrated...