Zoraida Callejas Carrión

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In this paper, we study the impact of considering context information for the annotation of emotions. Concretely, we propose the inclusion of the history of user–system interaction and the neutral speaking style of users. A new method to automatically include both sources of information has been developed making use of novel techniques for acoustic(More)
This paper proposes a new technique to test the performance of spoken dialogue systems by artificially simulating the behaviour of three types of user (very cooperative, cooperative and not very cooperative) interacting with a system by means of spoken dialogues. Experiments using the technique were carried out to test the performance of a previously(More)
The opinion mining and human-agent interaction communities are currently addressing sentiment analysis from different perspectives that comprise, on the one hand, disparate sentiment-related phenomena and computational representations, and on the other hand, different detection and dialog management methods. In this paper we identify and discuss the growing(More)
In this paper we propose a method for predicting the user mental state for the development of more efficient and usable spoken dialogue systems. This prediction, carried out for each user turn in the dialogue, makes it possible to adapt the system dynamically to the user needs. The mental state is built on the basis of the emotional state of the user and(More)
Ambient Intelligence (AmI) and Smart Environments (SmE) are based on three foundations: ubiquitous computing, ubiquitous communication and intelligent adaptive interfaces [41]. This type of systems consists of a series of interconnected computing and sensing devices which surround the user pervasively in his environment and are invisible to him, providing a(More)
This paper presents a new technique to enhance the performance of the input interface of spoken dialogue systems based on a procedure that combines during speech recognition the advantages of using prompt-dependent language models with those of using a language model independent of the prompts generated by the dialogue system. The technique proposes to(More)
This paper proposes a technique to correct speech recognition errors in spoken dialogue systems that presents two main novel contributions. On the one hand, it considers several contexts where a speech recognition result can be corrected. A threshold learnt in the training is used to decide whether the correction must be carried out in the context(More)
A domain-independent statistical methodology for dialog management in spoken dialog systems David Griol a,∗, Zoraida Callejas b, Ramón López-Cózar b, Giuseppe Riccardi c a Computer Science Department, Carlos III University of Madrid, Spain b Department of Languages and Computer Systems, University of Granada, Spain c Department of Information Engineering(More)