Forensic speaker verification using formant features and Gaussian mixture models

نویسندگان

  • Timo Becker
  • Michael Jessen
  • Catalin Grigoras
چکیده

A new method for speaker verification based on formant features is presented. A UBM-GMM verification system is applied to semi-automatically extracted formant features. Speakerspecific vocal tract configurations, including the speakers’ variability, are incorporated in the speaker models. Speaker comparisons are expressed as likelihood ratios (the ratio of similarity to typicality). F1, F2 and F3 values all enable speakers to be distinguished with a low error rate. The corresponding bandwidths further lower the error rate.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Formant 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 کامل

Speaker Recognition Using Gaussian Mixtures Models

Speech signal contains several levels of information. At first it contains information about the spoken message. At second level speech signal also gives information about the speaker identity, his emotional state and so on. The task of speaker recognition can be divided into two parts: speaker identification and speaker verification. Speaker identification is answering the question which one o...

متن کامل

Continuous prosodic features and formant modeling with joint factor analysis for speaker verification

In this paper, we introduced the use of formants contours with prosodic contours based on pitch and energy for speaker recognition. These contours are modeled on continuous manners by using the Legendre polynomials on basic unit which represents syllables. The parameters extracted from the Legendre polynomials coefficients plus the syllables duration are modeled with Gaussian Mixture Models (GM...

متن کامل

MLLR transforms as features in speaker recognition

We explore the use of adaptation transforms employed in speech recognition systems as features for speaker recognition. This approach is attractive because, unlike standard framebased cepstral speaker recognition models, it normalizes for the choice of spoken words in text-independent speaker verification. Affine transforms are computed for the Gaussian means of the acoustic models used in a re...

متن کامل

New background modeling for speaker verification

A new background speaker modelling method is presented in this paper for text-independent speaker verification using Gaussian mixture models. This method does not require speech databases of other speakers to build background speaker models. A background model can be built directly from the same claimed speaker's database and has a smaller number of Gaussian mixtures compared to the claimed spe...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2008