Raquel Justo

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In the framework of the DIHANA project, we present the acquisition process of a spontaneous speech dialogue corpus in Spanish. The selected application consists of information retrieval by telephone for nationwide trains. A total of 900 dialogues from 225 users were acquired using the Wizard of Oz technique. In this work, we present the design and planning(More)
Automatic detection of emotions like sarcasm or nastiness in online written conversation is a difficult task. It requires a system that can manage some kind of knowledge to interpret that emotional language is being used. In this work, we try to provide this knowledge to the system by considering alternative sets of features obtained according to different(More)
In this work, we propose and compare two different approaches to a two-level language model. Both of them are based on phrase classes but they consider different ways of dealing with phrases into the classes. We provide a complete formulation consistent with the two approaches. The language models proposed were integrated into an Automatic Speech(More)
In this work, we integrate phrases or segments of words into class n-gram language models in order to take advantage of two information sources: words and categories. Two different approaches to this kind of models are proposed and formulated. The models were integrated into an Automatic Speech Recognition system and subsequently evaluated in terms of word(More)
In this paper, a task of human-machine interaction based on speech is presented. The specific task consists on the use and control of a set of home appliances through a turn-based dialogue system. This work focuses on the first part of the dialogue system, the Automatic Speech Recognition (ASR) system. Two lines of work are taken into account to improve the(More)