The MIT lincoln laboratory 2008 speaker recognition system
نویسندگان
چکیده
In recent years methods for modeling and mitigating variational nuisances have been introduced and refined. A primary emphasis in this years NIST 2008 Speaker Recognition Evaluation (SRE) was to greatly expand the use of auxiliary microphones. This offered the additional channel variations which has been a historical challenge to speaker verification systems. In this paper we present the MIT Lincoln Laboratory Speaker Recognition system applied to the task in the NIST 2008 SRE. Our approach during the evaluation was two-fold: 1) Utilize recent advances in variational nuisance modeling (latent factor analysis and nuisance attribute projection) to allow our spectral speaker verification systems to better compensate for the channel variation introduced, and 2) fuse systems targeting the different linguistic tiers of information, high and low. The performance of the system is presented when applied on a NIST 2008 SRE task. Post evaluation analysis is conducted on the sub-task when interview microphones are present.
منابع مشابه
Partial Fulfillment of the Requirements for the Degrees of
With the dramatic increase in data volume, the automatic processing of this data becomes increasingly important. To process audio data, such as television and radio news broadcasts, speech recognizers have been used to obtain word transcriptions. Of late, new technologies have been developed to obtain speech metadata information, such as speaker segmentation, emotions, punctuation, et cetera. T...
متن کاملThe MIT-LL, JHU and LRDE NIST 2016 Speaker Recognition Evaluation System
In this paper, the NIST 2016 SRE system that resulted from the collaboration between MIT Lincoln Laboratory and the team at Johns Hopkins University is presented. The submissions for the 2016 evaluation consisted of three fixed condition submissions and a single system open condition submission. The primary submission on the fixed (and core) condition resulted in an actual DCF of .618. Details ...
متن کاملThe MMSR bilingual and crosschannel corpora for speaker recognition research and evaluation
We describe efforts to create corpora to support and evaluate systems that meet the challenge of speaker recognition in the face of both channel and language variation. In addition to addressing ongoing evaluation of speaker recognition systems, these corpora are aimed at the bilingual and crosschannel dimensions. We report on specific data collection efforts at the Linguistic Data Consortium, ...
متن کاملSpeaker Verification Using Adapted Gaussian Mixture Models
In this paper we describe the major elements of MIT Lincoln Laboratory’s Gaussian mixture model (GMM)-based speaker verification system used successfully in several NIST Speaker Recognition Evaluations (SREs). The system is built around the likelihood ratio test for verification, using simple but effective GMMs for likelihood functions, a universal background model (UBM) for alternative speaker...
متن کاملFormant and F0 Features for Speaker Verification
In this paper, the feature set of fundamental frequency, formant center frequencies, and formant bandwidths were used in speaker verification experiments using the database distributed by the Speaker Odyssey Workshop. The features were extracted using the Entropic Signal Processing System. The main classifier was a Gaussian Mixture Model system built by MIT Lincoln Laboratory, but tests were al...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2009