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Since emotions are expressed through a combination of verbal and non-verbal channels, a joint analysis of speech and gestures is required to understand expressive human communication. To facilitate such investigations, this paper describes a new corpus named the " interactive emotional dyadic motion capture database " (IEMOCAP), collected by the Speech(More)
UNLABELLED Inhibitory interneurons in the neocortex often connect in a promiscuous and extensive fashion, extending a "blanket of inhibition" on the circuit. This raises the problem of how can excitatory activity propagate in the midst of this widespread inhibition. One solution to this problem could be the vasoactive intestinal peptide (VIP) interneurons,(More)
SUMMARY TGF-b blockade significantly slows tumor growth through many mechanisms, including activation of CD8 + T cells and macrophages. Here, we show that TGF-b blockade also increases neutrophil-attracting chemo-kines, resulting in an influx of CD11b + /Ly6G + tumor-associated neutrophils (TANs) that are hypersegmented, more cytotoxic to tumor cells, and(More)
Many current state-of-the-art speaker diarization systems exploit agglomerative hierarchical clustering (AHC) as their speaker clustering strategy, due to its simple processing structure and acceptable level of performance. However, AHC is known to suffer from performance robustness under data source variation. In this paper, we address this problem. We(More)
Conflict is one of the most important phenomena of social life, but it is still largely neglected by the computing community. This work proposes an approach that detects common conversational social signals (loudness, overlapping speech, etc.) and predicts the conflict level perceived by human observers in continuous, non-categorical terms. The proposed(More)
Automatic analysis of spoken conversations has recently searched for phenomena like agreement/disagreement in collaborative and non-conflictual discussions (e.g., meetings). This work adds a novel dimension investigating conflicts in spontaneous conversations. The study makes use of broadcasted political debates where conflicts naturally arise between(More)
The goal of this work is to build a real-time emotion detection system which utilizes multi-modal fusion of different timescale features of speech. Conventional spectral and prosody features are used for intra-frame and supra-frame features respectively, and a new information fusion algorithm which takes care of the characteristics of each machine learning(More)
A new algorithm for content-based audio information retrieval is introduced in this work. Assuming that there exist hidden acoustic topics and each audio clip is a mixture of those acoustic topics, we proposed a topic model that learns a probability distribution over a set of hidden topics of a given audio clip in an unsupervised manner. We use the Latent(More)
OLAP queries (i.e. group-by or cube-by queries with ag-gregation) have proven to be valuable for data analysis and exploration. Many decision support applications need very complex OLAP queries, requiring a fine degree of control over both the group definition and the aggregates that are computed. For example, suppose that the user has access to a data cube(More)