2016
INTERSPEECH
INTERSPEECH 2016
Part-of-Speech Tagging and Chunking in Text-to-Speech Synthesis for South African Languages
Abstract
Text-to-speech synthesis can be an empowering communication tool in the hands of the print-disabled or augmentative and alternative communication user. In an effort to improve the naturalness of synthesised speech — and thus enhance the communication experience — we apply the natural language processing tasks of part-of-speech tagging and chunking to the text in the synthesis process. We cover the South African languages of (South African) English, Afrikaans, isiXhosa, isiZulu and Sepedi. The part-of-speech tagging delivers positive results for most of the languages; however, the chunking does not give any improvement in its current form.
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Conference Pioneer
— INTERSPEECH 2016
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Interdisciplinary Bridge
— Natural Language Processing and Speech & Audio
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Hot Topic Early Bird
— part-of-speech tagging
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio