Entity

Time filter

Source Type

Irun, Spain

De Ipina K.L.,University of the Basque Country | Hernandez C.,University of the Basque Country | Barroso N.,Irunweb Enterprise | Ezeiza A.,University of the Basque Country
Proceedings - International Carnahan Conference on Security Technology | Year: 2011

It Kokoro means, "heart" in Japanese. It also means "mind","soul", "sensibility", wishes and sentiments. All of these belong to the wide range of emotions and concepts that define the complex human condition. To be influenced by emotions is intrinsic to a human being. Emotions arise from having to face up to a changing and partially unpredictable world. This makes it necessary for all intelligent systems (whether natural or artificial) to develop emotions to survive [2]. Emotions are represented by the same subjective, cultural, physiological and behavioural components that express the perception of an individual's mental and physical state, and the way in which they interact with the environment. Then, how can we orientate Affective Computing? How can we fusion KOKORO and security context? Our system, KOKORO, analyses emotional expression based on ASR for Basque and Spanish users. Results are obtained over RekEmozio database [8] with SVM and HMMs. RekEmozio is a database of human emotions in Basque and Spanish (speech and video) with actors and amateurs. © 2011 IEEE. Source


Barroso N.,Irunweb Enterprise | De Ipina K.L.,University of the Basque Country | Hernandez C.,University of the Basque Country | Ezeiza A.,University of the Basque Country
Proceedings - International Carnahan Conference on Security Technology | Year: 2011

One of the goals of Speech Recognition Security (SRS) systems is to have appropriately tools to recognize speech password spoken based on elements such as words, sub-word or speakers. The main goal of the present work is to design robust ASR systems based on alternative ways to the classical evaluation rates, which often depend on the vocabulary of the task and on the language resources available. The drawback of this approach is that it is not straightforward that a system with a slightly lower WER during tests will adapt properly to new utterances, and this is much more sensible when the baseline system has a big error rate since there are many features that could be improved. This tends to be the case of under-resourced languages, since the lack of resources has a great impact in the performance of the system and not all the standard methods are suitable to any kind of language or task. The novel approach is to choose balanced multi-features of the acoustic models and the sub-word units based on rates related to entropy, mutual information and similitude. Selected models are integrated in an ontology-driven Audio Information Retrieval system that suits the requirements of under-resourced languages. © 2011 IEEE. Source


Barroso N.,Irunweb Enterprise | De Ipina K.L.,University of the Basque Country | Ezeiza A.,University of the Basque Country | Hernandez C.,University of the Basque Country
Proceedings - International Carnahan Conference on Security Technology | Year: 2011

It is significant to highlight that the demand of multilingual systems in human-computer interfaces is growing and automatic language identification (LID) is becoming increasingly important for the speech community as a fundamental tool to enrich theses systems. Research in this field has been active for several years. LID becomes also a useful resource in Multilingual Security System (MSS) providing methodologies to improve the robustness and the effectiveness of these systems. The main goal of our project is the development of Multilingual LVCSR systems in the Basque context. Nowadays, our work is oriented to the use of Basque in internet. The present work describes the development of a Language Identification (LID) system oriented to robust Multilingual Speech Recognition for under-resourced languages in the Basque context. © 2011 IEEE. Source


Barroso N.,Irunweb Enterprise | De Ipina K.L.,University of the Basque Country | Hernandez C.,University of the Basque Country | Ezeiza A.,University of the Basque Country
Proceedings - International Carnahan Conference on Security Technology | Year: 2011

The long term goal of our project is the development of robust Security Speech Recognition systems are based on Automatic Speech Recognition methodologies. The development of ASR systems involves dealing with issues such as Acoustic Phonetic Decoding (APD), Language Modelling (LM) or the development of appropriated Language Resources (LR). Thus these applications are generally very language-dependent and require very large resources. This work is focused to the selection of appropriated sub-word units with under-resourced and noisy conditions oriented to security tasks. The work has been carried out with a trilingual internet radio database. Thus, in order to decrease the negative impact that the lack of resources has in this issue we apply several data optimization methodologies based on Matrix Covariance Estimation and Ontology-based approaches. © 2011 IEEE. Source


Barroso N.,Irunweb Enterprise | De Ipina K.L.,University of the Basque Country | Grana M.,University of the Basque Country | Hernandez C.,University of the Basque Country
Advances in Intelligent and Soft Computing | Year: 2011

The development of Multilingual Automatic Speech Recognition (ASR) systems involves Acoustic Phonetic Decoding, Language Modeling, Language Identification and the development of appropriated Language Resources. Only a small number of languages possess the resources required for these developments, the remaining languages are under-resourced. In this paper we explore robust strategies of Soft Computing in the selection of sub-word units oriented to under-resourced languages for ASR in the Basque context. Three languages are analyzed: French, Spanish and the minority one, Basque language. The proposed methodology is based on approaches of Discriminant and Principal Components Analysis, robust covariance matrix estimation methods, Support Vector Machines (SVM), Hidden Markov Models (HMMs) and cross-lingual strategies. New methods improve considerably the accuracy rate obtained on incomplete, small sample sets, providing an excellent tool to manage these kinds of languages. © 2011 Springer-Verlag Berlin Heidelberg. Source

Discover hidden collaborations