Information based Speaker Verification
نویسندگان
چکیده
We discuss in this paper the conceptual and compu tational framework.of informatzon theory for decision making in speaker verification. The proposed approach departs itself from other conventional scoring models for speaker verification as the first approach takes into account the quantity of 'surprise' or information con tent. We compare the new approach with a widely used log-likelihood normalization method for speaker verifi cation. Experimental results on a commercial speech corpus validates the theoretical foundation of the pro posed method. Furthermore, we introduce the unique entropic measure of uncertainty in the verification scor mg.
منابع مشابه
Using Exciting and Spectral Envelope Information and Matrix Quantization for Improvement of the Speaker Verification Systems
Speaker verification from talking a few words of sentences has many applications. Many methods as DTW, HMM, VQ and MQ can be used for speaker verification. We applied MQ for its precise, reliable and robust performance with computational simplicity. We also used pitch frequency and log gain contour for further improvement of the system performance.
متن کاملUsing Exciting and Spectral Envelope Information and Matrix Quantization for Improvement of the Speaker Verification Systems
Speaker verification from talking a few words of sentences has many applications. Many methods as DTW, HMM, VQ and MQ can be used for speaker verification. We applied MQ for its precise, reliable and robust performance with computational simplicity. We also used pitch frequency and log gain contour for further improvement of the system performance.
متن کاملEffectiveness of Short-term Prosodic Features for Speaker Verification
In this work a traditional MFCC based speaker verification system is combined with a prosody based one to determine whether simple short-term prosodic information is useful for improving current state-of-theart ASV. The traditional speaker verification system based in spectral information has an EER of 3.85% when using 1024 mixtures. The prosody based system uses short-term intonation and energ...
متن کاملFusion of Cross Stream Information in Speaker Verification
This paper addresses the performance of various statistical data fusion techniques for combining the complementary score information in speaker verification. The complementary verification scores are based on the static and delta cepstral features. Both LPCC (Linear prediction-based cepstral coefficients) and MFCC (mel-frequency cepstral coefficients) are considered in the study. The experiment...
متن کاملDiscriminative adaptation for speaker verification
Speaker verification is a binary classification task to determine whether a claimed speaker uttered a phrase. Current approaches to speaker verification tasks typically involve adapting a general speaker Universal Background Model (UBM), normally a Gaussian Mixture Model (GMM), to model a particular speaker. Verification is then performed by comparing the likelihoods from the speaker model to t...
متن کاملSpeaker verification by integrating dynamic and static features using subspace method
In speaker recognition, it is a problem that variation of speech features is caused by sentences and time difference. Speech data includes a phonetic information and a speaker information. If they are separated each other, robust speaker verification will be realized by using only the speaker information. However, it is difficult to separate the speaker information from the phonetic information...
متن کامل