An investigation of supervector regression for forensic voice comparison on small data

International audienceThe present paper deals with an observer design for a nonlinear lateral vehicle model. The nonlinear model is represented by an exact Takagi-Sugeno (TS) model via the sector nonlinearity transformation. A proportional multiple integral observer (PMIO) based on the TS model is designed to estimate simultaneously the state vector and the unknown input (road curvature). The convergence conditions of the estimation error are expressed under LMI formulation using the Lyapunov theory which guaranties bounded error. Simulations are carried out and experimental results are provided to illustrate the proposed observer

A large-scale collaborative effort for noise-robust speaker verification

Contains fulltext : 116114.pdf (author's version ) (Open Access)Interspeech 2013, 25 augustus 201

Computationally efficient frame-averaged FM feature extraction for speaker recognition

Recently, subband frame-averaged frequency modulation (FM) as a complementary feature to amplitude-based features for several speech based classification problems including speaker recognition has shown promise. One problem with using FM extraction in practical implementations is computational complexity. Proposed is a computationally efficient method to estimate the frame-averaged FM component in a novel manner, using zero crossing counts and the zero crossing counts of the differentiated signal. FM components, extracted from subband speech signals using the proposed method, form a feature vector. Speaker recognition experiments conducted on the NIST 2008 telephone database show that the proposed method successfully augments mel frequency cepstrum coefficients (MFCCs) to improve performance, obtaining 17% relative reductions in equal error rates when compared with an MFCC-based system

Evaluation of a Fused FM and Cepstral-Based Speaker Recognition System on the NIST 2008 SRE

In this paper, the fusion of two speaker recognition subsystems, one based on Frequency Modulation (FM) and another on MFCC features, is reported. The motivation for their fusion was to improve the recognition accuracy across different types of channel variations, since the two features are believed to contain complementary information. It was found that the MFCC-based subsystem outperformed the FM-based subsystem on telephone conversations from NIST SRE-06 dataset, while the opposite was true for NIST SRE-08 telephone data. As a result, the FM-based subsystem performed as well as the MFCC-based subsystem and their fusion gave up to 23% relative improvement in terms of EER over the MFCC subsystem alone, when evaluated on the NIST 2008 core condition

I4U submission to NIST SRE 2012: A large-scale collaborative effort for noise-robust speaker verification

International audienceI4U is a joint entry of nine research Institutes and Universities across 4 continents to NIST SRE 2012. It started with a brief discussion during the Odyssey 2012 workshop in Singapore. An online discussion group was soon set up, providing a discussion platform for different issues surrounding NIST SRE'12. Noisy test segments, uneven multi-session training, variable enrollment duration, and the issue of open-set identification were actively discussed leading to various solutions integrated to the I4U submission. The joint submission and several of its 17 subsystems were among top-performing systems. We summarize the lessons learnt from this large-scale effort

I4U submission to NIST SRE 2012: A large-scale collaborative effort for noise-robust speaker verification

I4U is a joint entry of nine research Institutes and Universities across 4 continents to NIST SRE 2012. It started with a brief discussion during the Odyssey 2012 workshop in Singapore. An online discussion group was soon set up, providing a discussion platform for different issues surrounding NIST SRE’12. Noisy test segments, uneven multi-session training, variable enrollment duration, and the issue of open-set identification were actively discussed leading to various solutions integrated to the I4U submission. The joint submission and several of its 17 subsystems were among top-performing systems. We summarize the lessons learnt from this large-scale effort