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Cyberbullying is the use of digital media to harass a person or group of people, through personal attacks, disclosure of confidential or false information, among other means. That is to say, it is considered cyberbullying, or cyber-aggression to everything that is done through electronic communication devices with the intended purpose of harming or attacking a person or a group.In this paper we present a starting project to prevent cyberbullying between kids and teenagers. The idea is to create a prevention system. A system which is installed in the mobile of a kid and, if a harassment is detected, some advice is given to the child. In case of serious or repeated behavior the parents are alerted. The focus of this paper is to describe the characteristics of the database to be used to train the system, Peer Reviewed, Postprint (published version)

This paper is focused on the application of the Language Identification (LID) technology for intelligent vehicles. We cope with short sentences or words spoken in moving cars in four languages: English, Spanish, German, and Finnish. As the response time of the LID system is crucial for user acceptance in this particular task, speech signals of different durations with total average of 3.8s are analyzed. In this paper, the authors propose the use of Deep Neural Networks (DNN) to model effectively the i-vector space of languages. Both raw i-vectors and session variability compensated i-vectors are evaluated as input vectors to DNNs. The performance of the proposed DNN architecture is compared with both conventional GMM-UBM and i-vector/LDA systems considering the effect of durations of signals. It is shown that the signals with durations between 2 and 3s meet the requirements of this application, i.e., high accuracy and fast decision, in which the proposed DNN architecture outperforms GMM-UBM and i-vector/LDA systems by 37% and 28%, respectively., Peer Reviewed, Postprint (published version)

It is well known that canonical Spanish, the dialectal variant `central' of Spain, so called Castilian, can be transcribed by rules. This paper deals with the automatic grapheme to phoneme transcription rules in several Spanish dialects from Latin America. Spanish is a language spoken by more than 300 million people, has an important geographical dispersion compared among other languages and has been historically influenced by many native languages. In this paper authors expand the Castilian transcription rules to a set of different dialectal variants of Latin America. Transcriptions are based on SAMPA symbols. The paper includes an identification of sounds that doesn't appear in Castilian, extend accepted SAMPA symbols for Spanish (Castilian) to different dialectal variants, describes the necessary rules to implement an automatic Orthographic to Phonetic transcription in several dialectal Spanish variants and show some quantitative results of dialectal differences., Peer Reviewed, Postprint (published version)