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We propose a method for computing semantic relatedness between words or texts by using knowledge from hypertext encyclopedias such as Wikipedia. A network of concepts is built by filtering the encyclopedia's articles, each concept corresponding to an artic ...
Standard hidden Markov model (HMM) based automatic speech recognition (ASR) systems use phonemes as subword units. Thus, development of ASR system for a new language or domain depends upon the availability of a phoneme lexicon in the target language. In th ...
The paper presents machine translation experiments from English to Czech with a large amount of manually annotated discourse connectives. The gold-standard discourse relation annotation leads to better translation performance in ranges of 4–60% for some am ...
This paper introduces a new dataset and compares several methods for the recommendation of non-fiction audio-visual material, namely lectures from the TED website. The TED dataset contains 1,149 talks and 69,023 user profiles, who have made more than 100,0 ...
Standard automatic speech recognition (ASR) systems use phonemes as subword units. Thus, one of the primary resource required to build a good ASR system is a well developed phoneme pronunciation lexicon. However, under-resourced languages typically lack su ...
This paper addresses the problem of evaluating and estimating the mechanical robustness of footholds for legged robots in unstructured terrain. In contrast to approaches that rely on human expert knowledge or human defined criteria to identify appropriate ...
In this thesis, we propose novel solutions to similarity learning problems on collaborative networks. Similarity learning is essential for modeling and predicting the evolution of collaborative networks. In addition, similarity learning is used to perform ...
In this paper, we detail a method for domain specific, multi-category emotion recognition, based on human computation. We create an Amazon Mechanical Turk1 task that elicits emotion labels and phrase-emotion associations from the participants. Using the pr ...
Our research addresses the need for an efficient, effective, and interactive access to large-scale image collections. Image retrieval needs are evolving beyond the capabilities of the traditional indexing based on manual annotation, and the most desirable ...
This paper proposes a control scheme for distributed sensing using a leader/follower multi-agent architecture. The control objective is to make a group of mobile agents cover and sense a sequence of regions of interest. More specifically, when the leaders ...
