Incorporating Prosodic with Acoustic information for ISCSLP’2006 Speaker Recognition Evaluation- Robust Cross-Channel Speaker Verification

Speaker Verification Using Complementary Information from Vocal Source and Vocal Tract

This paper describes a speaker verification system which uses two complementary acoustic features: Mel-frequency cepstral coefficients (MFCC) and wavelet octave coefficients of residues (WOCOR). While MFCC characterizes mainly the spectral envelope, or the formant structure of the vocal tract system, WOCOR aims at representing the spectro-temporal characteristics of the vocal source excitation....

結合韻律與聲學訊息之強健性漢語語者驗證系統 (Incorporating Prosodic with Acoustic information for Robust Speaker Verification) [In Chinese]

ISCSLP SR Evaluation, UVA-CS_es System Description. A System Based on ANNs

This paper shows a description of the system used in the ISCSLP06 Speaker Recognition Evaluation, text independent cross-channel speaker verification task. It is a discriminative Artificial Neural Networkbased system, using the Non-Target Incremental Learning method to select world representatives. Two different training strategies have been followed: (i) to use world representative samples wit...

A Review of Various Score Normalization Techniques for Speaker Identification System

This paper presents an overview of a state-of-the-art text-independent speaker verification system using score normalization. First, an introduction proposes a modular scheme of the training and test phases of a speaker verification system. Then, the most commonly speech parameterization used in speaker verification, namely, cepstral analysis, is detailed. Normalization of scores is then explai...

Duration and pronunciation conditioned lexical modeling for speaker verification

We propose a method to improve speaker recognition lexical model performance using acoustic-prosodic information. More specifically, the lexical model is trained using durationand pronunciation-conditioned word N-grams, simultaneously modeling lexical information along with their acoustic and prosodic characteristics. Support vector machines are used for modeling and scoring, with N-gram freque...