Accession Number:

AD1033868

Title:

The MITLL NIST LRE 2015 Language Recognition system

Descriptive Note:

[Technical Report, Technical Paper]

Corporate Author:

MASSACHUSETTS INST OF TECH LEXINGTON

Personal Author(s):

• Torres-Carrasquillo, Pedro A.
• Godoy, Elizabeth C.
• Reynolds, Douglas A.
• Richardson, Frederick S.
• Singer, Elliot
• Sturim, Douglas E.

Report Date:

2016-02-05

Pagination or Media Count:

8

Abstract:

In this paper we describe the most recent MIT Lincoln Laboratory language recognition system developed for the NIST 2015 Language Recognition Evaluation LRE. The submission features a fusion of five core classifiers, with most systems developed in the context of an i-vector framework. The 2015 evaluation presented new paradigms. First, the evaluation included fixed training and open training tracks for the first time second, language classification performance was measured across 6 language clusters using 20 language classes instead of an N-way language task and third, performance was measured across a nominal 3-30 second range. Results are presented for the average performance across the 6 language clusters for both the fixed and open training tasks. On the 6-cluster metric the Lincoln system achieved average costs of 0.173 and 0.168 for the fixed and open tasks respectively.

Descriptors:

• artificial neural networks
• artificial intelligence
• recognition
• language
• statistics
• computer science
• digital data
• training
• standards
• test sets
• discriminant analysis
• monte carlo method
• observation
• order statistics
• test and evaluation
• algorithms
• calibration
• classification
• detection
• feature extraction

Subject Categories:

• Cybernetics
• Linguistics

Distribution Statement:

[A, Approved For Public Release]