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Peisenieks J.,University of Latvia | Skadins R.,Tilde
Frontiers in Artificial Intelligence and Applications | Year: 2014

This paper reports on the viability of using machine translation (MT) for determining the original sentiment of tweets, when translating tweets made in internationally less used language into more frequently used ones. The results of the study show that it is possible to use MT and sentiment analysis (SA) systems to produce SA results with significant precision. © 2014 The Authors and IOS Press. Source


Pinnis M.,Tilde | Pinnis M.,University of Latvia
Frontiers in Artificial Intelligence and Applications | Year: 2014

Transliteration dictionaries are an important resource for the development of machine transliteration systems. The paper describes and analyses a large multilingual transliteration dictionary extracted from probabilistic dictionaries for 24 European languages containing approximately 1.25 million transliterated word pairs. The transliteration dictionary is evaluated: 1) manually for the Latvian-English language pair and 2) automatically within a statistical machine translation based transliteration task for all 23 language pairs. © 2014 The Authors and IOS Press. Source


Vira I.,Tilde | Vasiljevs A.,Tilde
Frontiers in Artificial Intelligence and Applications | Year: 2014

In this paper we present two prototypes of 3D based virtual agents: one chatbot which in addition to the ability to hold a conversation can perform translation from English into Spanish, Russian, and French; and another which supplies currency conversion (lats to euro and euro to lats) in the Latvian language. Both chatbots are voice controlled, with natural mimicry and representations of human-like emotions. We describe the motivation, development process, design and architecture of these mobile applications. The evaluation of both applications and their usage in selected scenarios is also presented. © 2014 The Authors and IOS Press. Source


Salimbajevs A.,Tilde | Pinnis M.,Tilde
Frontiers in Artificial Intelligence and Applications | Year: 2014

In this paper, the authors present the results of ongoing research on Large Vocabulary Automatic Speech Recognition for the Latvian language. The paper describes the initial acoustic model, phoneme set, filler and noise models, and grapheme-to-phoneme modelling. The second part of this work is focused on language modelling. Different word and class-based n-gram models are evaluated in terms of perplexity and word error rate in a speech recognition task. The authors also train a recurrent neural network language model and use it for n-best rescoring. © 2014 The Authors and IOS Press. Source


Deksne D.,Tilde | Skadins R.,Tilde
Frontiers in Artificial Intelligence and Applications | Year: 2012

In this paper, we present the results of a series of experiments done to improve the quality of a Lithuanian-English statistical MT (SMT) system. We particularly focus on word alignment and out of vocabulary issues in SMT translating from a morphologically rich language into English. © 2012 The Authors and IOS Press. Source

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