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We present a computational approach for predicting the popularity score of sneakers through the analysis of growing amount of online data. Sneakers are described in several aspects based on which a popularity prediction model is constructed. In particular, we utilize the multiple kernel learning technique with customized kernels to analyze multimodal data extracted from an online sneaker magazine...
This study proposes a data-driven approach to phone set construction for code-switching automatic speech recognition (ASR). Acoustic and context-dependent cross-lingual articulatory features (AFs) are incorporated into the estimation of the distance between triphone units for constructing a Chinese-English phone set. The acoustic features of each triphone in the training corpus are extracted for constructing...
Bilingual speakers are known for their ability to code-switch or mix their languages during communication. This phenomenon occurs when bilinguals substitute a word or phrase from one language with a phrase or word from another language. For code-switching speech recognition, it is essential to collect a large-scale code-switching speech database for model training. In order to ease the negative effect...
Assessing and selecting relevant visual cues is crucial for rapid saliency estimation and visual search. Here, we derive a new optimal feature modulation strategy to maximize the relative salience of the target, in which the top-down weight on a feature map depends on its stimulation intensity ratio (SIR) between the target and the distractors. The stimulation intensity is determined by two factors,...
In this paper, we propose a learning-based system for generating exaggerative caricatures with expression. Most of the previous works can only deal with frontal face images with neutral expression without glasses or hats, and are unable to apply more than one drawing prototype which was learned from the caricatures drawn by one single cartoonist at a time. The proposed caricature generation system...
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