Music and Audio Processing

We propose a fully automatic and computationally efficient framework for analysis and summarization of soccer videos using cinematic and object-based features. The proposed framework includes some novel low-level processing algorithms, such as dominant color region detection, robust shot boundary detection, and shot c…

We propose a fully automatic and computationally efficient framework for analysis and summarization of soccer videos using cinematic and object-based features. The proposed framework includes some novel low-level processing algorithms, such as dominant color region detection, robust shot boundary detection, and shot c…

• AHMET MURAT TEKALP

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• MUHAMMED FATİH DEMİRCİ

The performance of biometric systems based on automatic speaker recognition technology is severely degraded due to spoofing attacks with synthetic speech generated using different voice conversion (VC) and speech synthesis (SS) techniques. Various countermeasures are proposed to detect this type of at-tack, and in thi…

Time series classification is an important task with many challenging applications. A nearest neighbor (NN) classifier with dynamic time warping (DTW) distance is a strong solution in this context. On the other hand, feature-based approaches have been proposed as both classifiers and to provide insight into the series…

• MUSTAFA GÖKÇE BAYDOĞAN

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• BİLAL ALATAŞ

Concerns regarding the vulnerability of automatic speaker verification (ASV) technology against spoofing can undermine confidence in its reliability and form a barrier to exploitation. The absence of competitive evaluations and the lack of common datasets has hampered progress in developing effective spoofing counterm…

• CEMAL HANİLÇİ

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• KEMAL POLAT

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• CEMAL OKAN ŞAKAR

Deep learning can be used for audio signal classification in a variety of ways. It can be used to detect and classify various types of audio signals such as speech, music, and environmental sounds. Deep learning models are able to learn complex patterns of audio signals and can be trained on large datasets to achieve…

It is well-known that early integration (also called data fusion) is effective when the modalities are correlated, and late integration (also called decision or opinion fusion) is optimal when modalities are uncorrelated. In this paper, we propose a new multimodal fusion strategy for open-set speaker identification us…

• YÜCEL YEMEZ

It is well-known that early integration (also called data fusion) is effective when the modalities are correlated, and late integration (also called decision or opinion fusion) is optimal when modalities are uncorrelated. In this paper, we propose a new multimodal fusion strategy for open-set speaker identification us…

• ENGİN ERZİN