OVERLAPPED-SPEECH DETECTION WITH APPLICATIONS TO DRIVER ASSESSMENT FOR IN-VEHICLE ACTIVE SAFETY SYSTEMS

ABSTRACT In this study we propose a system for overlapped-speech detection. Spectral harmonicity and envelope features are extracted to represent overlapped and single-speaker speech using Gaussian mixture models (GMM). The system is shown to effectively discriminate the single and overlapped speech classes. We further increase the discrimination by proposing a phoneme selection scheme to generate more reliable artificial overlapped data for model training. Evaluations on artificially generated co-channel data show that the novelty in feature selection and phoneme omission results in a relative improvement of 10% in the detection accuracy compared to baseline. As an example application, we evaluate the effectiveness of overlapped-speech detection for vehicular environments and its potential in assessing driver alertness. Results indicate a good correlation between driver performance and the amount and location of overlapped-speech segments

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

The submission of I4U, is a joint effort of nine research Institutes and Universities across 4 continents for submitting speaker recognition results to NIST SRE 2012. The joint efforts were started with a brief discussion during the Odyssey 2012 workshop in Singapore. An online discussion group was soon set up afterwards, providing a discussion platform for different issues surrounding the NIST SRE’12. In particular, noisy test segments, uneven multi-session training, variable enrollment duration, and the issue of open-set identification have been actively discussed. Various solutions were put in place as part of the I4U submission. The submission of I4U as well as several individual submissions from coalition members, was found to be among top-performing systems submitted to SRE’12. This paper summarizes the system components’ details for 17 systems included in I4U submission

CRSS systems for 2012 NIST speaker recognition evaluation

This paper describes the systems developed by the Center fo

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 sub-systems were among top-performing systems. We summarize the lessons learnt from this large-scale effort