Data Set Used
This paper presents an overview of the architecture and algorithms implemented in IBM's text-independent speaker veriication system developed for the 2002 NIST Speaker Recognition Evaluation, particularly for the 1-speaker detection task using cellular test data. We describe individual components including a Gaussianization front-end, celluar-codec… (More)
Although the last decade has witnessed mounting research on the development and evaluation of positive interventions, investigators still know little about the target population of such interventions: happiness seekers. The present research asked three questions about happiness seekers: (1) What are their general characteristics?, (2) What do they… (More)
accuracy and the computational requirements are estimated. Co-variance modeling is seen to be a viable alternative to GMM whenever computational and storage requirements must to be traded with verification accuracy.
—This paper describes a computationally simple method to perform text independent speaker verification using second order statistics. The suggested method, called utterance level scoring (ULS), allows obtaining a normalized score using a single pass through the frames of the tested utterance. The utterance sample covariance is first calculated and then… (More)
The paper considers text independent speaker identification over the telephone using short training and testing data. Gaussian Mixture Modeling (GMM) is used in the testing phase, but the parameters of the model are taken from clusters obtained for the training data by an adequate choice of feature vectors and a distance measure without optimization in the… (More)