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This paper describes a new database for the assessment of automatic speaker verification (ASV) vulnerabilities to spoofing attacks. In contrast to other recent data collection efforts, the new database has been designed to support the development of replay spoofing countermeasures tailored towards the protection of text-dependent ASV systems from replay attacks in the face of variable recording and...
With the development of speech synthesis techniques, automatic speaker verification systems face the serious challenge of spoofing attack. In order to improve the reliability of speaker verification systems, we develop a new filter bank-based cepstral feature, deep neural network (DNN) filter bank cepstral coefficients, to distinguish between natural and spoofed speech. The DNN filter bank is automatically...
Many researchers have demonstrated the good performance of spoofing detection systems under clean training and testing conditions. However, it is well known that the performance of speaker and speech recognition systems significantly degrades in noisy conditions. Therefore, it is of great interest to investigate the effect of noise on the performance of spoofing detection systems. In this paper, we...
Person identification is a very important task for intelligent devices when communicating or interacting with humans. A potential problem in real applications is that the amount of enrollment data is insufficient. When multiple modalities are available, it is possible to re-train the system online by exploiting the conditional independence between the modalities and thus improving classification accuracy...
Emotion recognition in speech is a very challenging task in the speech processing domain. Because of the continuity characteristics of human emotion, most of the recent research focuses on recognising emotion in a continuous space. While previous attempts for speech emotion annotation adopted the likert-like scaling system in a continuous space and relied on prediction models to predict emotion we,...
AMORE is a hybrid recommendation system that provides movie recommendations for a major triple-play services provider in Greece. Combined with our own implementations of several user-, item-, and content-based recommendation algorithms, AMORE significantly outperforms other state-of-the-art implementations both in solution quality and response time. AMORE currently serves daily recommendation requests...
In this paper we propose a web log mining-based network user behavior analysis scheme, which plays an important role in network structure optimization and website server configuration. Based on clustering and regression model, we studied the network user's visit model in a university by analyzing a large amount of web log data which is collected from the university campus network. The data analyzing...
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