A Simple Spanish Part of Speech Tagger for Detection and Correction of Accentuation Error
TSD '99 Proceedings of the Second International Workshop on Text, Speech and Dialogue
Letter level learning for language independent diacritics restoration
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Spectrum Modification for Emotional Speech Synthesis
Multimodal Signals: Cognitive and Algorithmic Issues
Corpus-Based unit selection TTS for hungarian
TSD'06 Proceedings of the 9th international conference on Text, Speech and Dialogue
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This paper gives an overview of the design concepts and implementation of a Hungarian microblog reading system. Speech synthesis of such special text requires some special components. First, an efficient diacritic reconstruction algorithm was applied. The accuracy of a former dictionary-based method was improved by machine learning to handle ambiguous cases properly. Second, an unlimited domain text-to-speech synthesizer was applied with extensions for emotional and spontaneous styles. Chat or blog texts often contain "emoticons" which mark the emotional state of the user. Therefore, an expressive speech synthesis method was adapted to a corpus-based synthesizer. Four emotions were generated and evaluated in a listening test: neutral, happy, angry and sad. The results of the experiments showed that happy and sad emotions can be generated with this algorithm, with best accuracy for female voice.