Proposal for a High Energy Nuclear Database

We propose to develop a high-energy heavy-ion experimental database and make it accessible to the scientific community through an on-line interface. This database will be searchable and cross-indexed with relevant publications, including published detector descriptions. Since this database will be a community resource, it requires the high-energy nuclear physics community's financial and manpower support. This database should eventually contain all published data from Bevalac, AGS and SPS to RHIC and LHC energies, proton-proton to nucleus-nucleus collisions as well as other relevant systems, and all measured observables. Such a database would have tremendous scientific payoff as it makes systematic studies easier and allows simpler benchmarking of theoretical models to a broad range of old and new experiments. Furthermore, there is a growing need for compilations of high-energy nuclear data for applications including stockpile stewardship, technology development for inertial confinement fusion and target and source development for upcoming facilities such as the Next Linear Collider. To enhance the utility of this database, we propose periodically performing evaluations of the data and summarizing the results in topical reviews.Comment: 8 pages, 3 figures. Proceedings of the 21st Winter Workshop on Nuclear Dynamics, Breckenridge, Colorado, February 5--12, 200

A High Energy Nuclear Database Proposal

We propose to develop a high-energy heavy-ion experimental database and make it accessible to the scientific community through an on-line interace. This database will be searchable and cross-indexed with relevant publications, including published detector descriptions. Since this database will be a community resource, it requires the high-energy nuclear physics community's financial and manpower support. This database should eventually contain all published data from the Bevalac, AGS and SPS to RHIC and LHC energies, proton-proton to nucleus-nucleus collisions as well as other relevant systems and all measured observables. Such a database would have tremendous scientific payoff as it makes systematic studies easier and allows simpler benchmarking of theoretical models to a broad range of old and new experiments. Furthermore, there is a growing need for compilations of high-energy nuclear data for applications including stockpile stewardship, technology development for intertial confinement fusion and target and source development for upcoming facilities such as the Next Linear Collider. To enhance the utility of this database, we propose periodically performing evaluations of the data and summarizing the results in topical reviews.Comment: 4 pages, poster proceedings from Quark Matter 200

Cross likelihood ratio based speaker clustering using eigenvoice models

This paper proposes the use of eigenvoice modeling techniques with the Cross Likelihood Ratio (CLR) as a criterion for speaker clustering within a speaker diarization system. The CLR has previously been shown to be a robust decision criterion for speaker clustering using Gaussian Mixture Models. Recently, eigenvoice modeling techniques have become increasingly popular, due to its ability to adequately represent a speaker based on sparse training data, as well as an improved capture of differences in speaker characteristics. This paper hence proposes that it would be beneficial to capitalize on the advantages of eigenvoice modeling in a CLR framework. Results obtained on the 2002 Rich Transcription (RT-02) Evaluation dataset show an improved clustering performance, resulting in a 35.1% relative improvement in the overall Diarization Error Rate (DER) compared to the baseline system