Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: automatic speaker verification

Sortuj według:

Ogranicz wyniki do:

The Effect of Voice over IP Transmission Degradations on MAP-EM-GMM Speaker Verification Performance

Maciejko W.

Archives of Acoustics

2015

Vol. 40, No. 3

407--417

Despite the growing importance of packet switching systems, there is still a shortage of thorough analyses of VoIP transmission effect on speech and speaker recognition performance. Voice over IP transmission systems use packet switching. There is no guarantee of delivery. The main disadvantage of VoIP is a packet loss which has a major impact on the performance experienced by the users of the network. There are several techniques to mask the effects of a packet loss, referred to as packet loss concealment. In this study, the effect of voice transmission over IP on automatic speaker verification system performance was investigated. The analyzed system was based on MAP-EM-GMM modelling methods. Four various speech codecs of H.323 standard were investigated with special emphasis placed on the packet loss phenomenon and various packet loss concealment techniques.

An improved ant colony optimization algorithm and its application to text-independent speaker verification system

Aghdam M. H.

Journal of Artificial Intelligence and Soft Computing Research

2012

Vol. 2, No. 4

301--315

With the growing trend toward remote security verification procedures for telephone banking, biometric security measures and similar applications, automatic speaker verification (ASV) has received a lot of attention in recent years. The complexity of ASV system and its verification time depends on the number of feature vectors, their dimensionality, the complexity of the speaker models and the number of speakers. In this paper, we concentrate on optimizing dimensionality of feature space by selecting relevant features. At present there are several methods for feature selection in ASV systems. To improve performance of ASV system we present another method that is based on ant colony optimization (ACO) algorithm. After feature selection phase, feature vectors are applied to a Gaussian mixture model universal background model (GMM-UBM) which is a text-independent speaker verification model. The performance of proposed algorithm is compared to the performance of genetic algorithm on the task of feature selection in TIMIT corpora. The results of experiments indicate that with the optimized feature set, the performance of the ASV system is improved. Moreover, the speed of verification is significantly increased since by use of ACO, number of features is reduced over 80% which consequently decrease the complexity of our ASV system.