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    Wyświetlanie 1-5 z 5
    Tytuł:
    Joint Factor Analysis of Channel Mismatch in Whispering Speaker Verification
    Autorzy:
    Lv, G
    Zhao, H.
    Powiązania:
    https://bibliotekanauki.pl/articles/176713.pdf
    Data publikacji:
    2012
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    joint factor analysis
    whisper
    speaker verification
    Opis:
    A speaker recognition system based on joint factor analysis (JFA) is proposed to improve whisper- ing speakers’ recognition rate under channel mismatch. The system estimated separately the eigenvoice and the eigenchannel before calculating the corresponding speaker and the channel factors. Finally, a channel-free speaker model was built to describe accurately a speaker using model compensation. The test results from the whispered speech databases obtained under eight different channels showed that the correct recognition rate of a recognition system based on JFA was higher than that of the Gaussian Mixture Model–Universal Background Model. In particular, the recognition rate in cellphone channel tests increased significantly.
    Źródło:
    Archives of Acoustics; 2012, 37, 4; 555-559
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Speaker Model Clustering to Construct Background Models for Speaker Verification
    Autorzy:
    Dişken, G.
    Tüfekci, Z.
    Çevik, U.
    Powiązania:
    https://bibliotekanauki.pl/articles/177299.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    Gaussian mixture models
    k-means
    imposter models
    speaker clustering
    speaker verification
    Opis:
    Conventional speaker recognition systems use the Universal Background Model (UBM) as an imposter for all speakers. In this paper, speaker models are clustered to obtain better imposter model representations for speaker verification purpose. First, a UBM is trained, and speaker models are adapted from the UBM. Then, the k-means algorithm with the Euclidean distance measure is applied to the speaker models. The speakers are divided into two, three, four, and five clusters. The resulting cluster centers are used as background models of their respective speakers. Experiments showed that the proposed method consistently produced lower Equal Error Rates (EER) than the conventional UBM approach for 3, 10, and 30 seconds long test utterances, and also for channel mismatch conditions. The proposed method is also compared with the i-vector approach. The three-cluster model achieved the best performance with a 12.4% relative EER reduction in average, compared to the i-vector method. Statistical significance of the results are also given.
    Źródło:
    Archives of Acoustics; 2017, 42, 1; 127-135
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The Effect of Voice over IP Transmission Degradations on MAP-EM-GMM Speaker Verification Performance
    Autorzy:
    Maciejko, W.
    Powiązania:
    https://bibliotekanauki.pl/articles/177874.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    automatic speaker verification
    packet loss
    speech compression
    voice over IP
    Opis:
    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.
    Źródło:
    Archives of Acoustics; 2015, 40, 3; 407-417
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    SpeakerNet for Cross-lingual Text-Independent Speaker Verification
    Autorzy:
    Habib, Hafsa
    Tauseef, Huma
    Fahiem, Muhammad Abuzar
    Farhan, Saima
    Usman, Ghousia
    Powiązania:
    https://bibliotekanauki.pl/articles/1953543.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    convolutional neural network
    deep learning
    Siamese network
    speaker verification
    text-independent
    binary operation
    Urdu speaker recognition
    Opis:
    Biometrics provide an alternative to passwords and pins for authentication. The emergence of machine learning algorithms provides an easy and economical solution to authentication problems. The phases of speaker verification protocol are training, enrollment of speakers and evaluation of unknown voice. In this paper, we addressed text independent speaker verification using Siamese convolutional network. Siamese networks are twin networks with shared weights. Feature space can be learnt easily by training these networks even if similar observations are placed in proximity. Extracted features from Siamese then can be classified using difference or correlation measures. We have implemented a customized scoring scheme that utilizes Siamese’ capability of applying distance measures with the convolutional learning. Experiments made on cross language audios of multi-lingual speakers confirm the capability of our architecture to handle gender, age and language independent speaker verification. Moreover, our designed Siamese network, SpeakerNet, provided better results than the existing speaker verification approaches by decreasing the equal error rate to 0.02.
    Źródło:
    Archives of Acoustics; 2020, 45, 4; 573-583
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    An improved ant colony optimization algorithm and its application to text-independent speaker verification system
    Autorzy:
    Aghdam, M. H.
    Powiązania:
    https://bibliotekanauki.pl/articles/91678.pdf
    Data publikacji:
    2012
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    ant colony
    optimization
    ant colony optimization
    ACO
    security
    automatic speaker verification
    ASV
    feature space
    Gaussian mixture model universal background model
    GMM-UBM
    Opis:
    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.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2012, 2, 4; 301-315
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-5 z 5

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