Electrolaryngeal (EL) speech produced by a laryngectomee using an electrolarynx to mechanically generate artificial excitation sounds severely suffers from unnatural fundamental frequency (F0) patterns caused by monotonic excitation sounds. To address this issue, we have previously proposed EL speech enhancement systems using statistical F0 pattern prediction methods based on a Gaussian Mixture...

Speech based cognitive load estimation is a new field of research. Due to this relative ‘lack of maturity’, a single best approach to building cognitive load estimation systems has not been established yet. The primary aim of this submission is to report the performance of various basic utterance level classification frameworks developed using important elements of state-of-the-art speaker reco...

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy GAUSSIAN MIXTURE MODEL BASED SYSTEM IDENTIFICATION AND CONTROL By Jing Lan August 2006 Chair: José C. Principe Major Department: Electrical and Computer Engineering In this dissertation, we present a methodology of combining an improved ...

It is shown that e¢ cient GMM (generalized method of moments) estimation of a linear model corresponds to standard IV (instrumental variables) estimation of this model, after transforming it such (as in GLS) that its resulting disturbances have a scalar covariance matrix, while using as instruments the original instruments linearly transformed by the transpose of the inverse of the matrix used ...

The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to the...

An automatic Language Identification (LID) is the task of automatically recognizing a language from the given spoken utterance. Language identification is used to identify the language of the particular audio and reduce the complexity of the audio sample. LID systems that rely on multiple language phone recognition language modeling (PRLM) and n-gram language modeling produces the best performa...

In this study, we develop a new system for real world audio environment matching. Environment detection within unknown audio streams requires a system that operates in an unsupervised manner since it will be faced with unknown environments without prior information. In addition, the overall solution should be computationally efficient for large audio collection. In the proposed approach, a Gaus...

This paper presents a new approach to modeling speech spectra and pitch for text-independent speaker identification using Gaussian mixture models based on multi-space probability distribution (MSD-GMM). The MSD-GMM allows us to model continuous pitch values for voiced frames and discrete symbols representing unvoiced frames in a unified framework. Spectral and pitch features are jointly modeled...

In this gives an overview of automatic speaker recognition technology, with an emphasis on textindependent recognition. Speaker recognition has been studied actively for several decades. We give an overview of both the classical and the state-of-the-art methods. We start with the fundamentals of automatic speaker recognition, concerning feature extraction and speaker modeling. Here, describe a ...