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Language independent query-by-example spoken term detection (QbE-STD) is the problem of retrieving audio documents from an archive, which contain a spoken query provided by a user. This is usually casted as a hypothesis testing and pattern matching problem ...
Increasing concerns with privacy have stimulated interests in Session-based Recommendation (SR) using no personal data other than what is observed in the current browser session. Existing methods are evaluated in static settings which rarely occur in real- ...
Robustness of extracted embeddings in cross-database scenarios is one of the main challenges in text-independent speaker verification (SV) systems. In this paper, we investigate this robustness via performing structural cross-database experiments with or w ...
With ever greater computational resources and more accessible software, deep neural networks have become ubiquitous across industry and academia.
Their remarkable ability to generalize to new samples defies the conventional view, which holds that complex, ...
This work focuses on detecting presentation attacks (PA) mounted using custom silicone masks. Face recognition (FR) systems have been shown to be highly vulnerable to PAs based on such masks [1, 2]. Here
we explore the use of multispectral data (color imag ...
We experiment with subword segmentation approaches that are widely used to address the open vocabulary problem in the context of end-to-end automatic speech recognition (ASR). For morphologically rich languages such as German which has many rare words main ...
Existing deep architectures cannot operate on very large signals such as megapixel images due to computational and memory constraints. To tackle this limitation, we propose a fully differentiable end-to-end trainable model that samples and processes only a ...
In this paper, we propose a novel temporal spiking recurrent neural network (TSRNN) to perform robust action recognition in videos. The proposed TSRNN employs a novel spiking architecture which utilizes the local discriminative features from high-confidenc ...
Transportation systems often rely on understanding the flow of vehicles or pedestrian. From traffic monitoring at the city scale, to commuters in train terminals, recent progress in sensing technology make it possible to use cameras to better understand th ...
Due to their wide field of view, omnidirectional cameras are frequently used by autonomous vehicles, drones and robots for navigation and other computer vision tasks. The images captured by such cameras, are often analyzed and classified with techniques de ...