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Conditional Random Fields Applied to Arabic Orthographic-Phonetic Transcription

Cherifi El-Hadi, Guerti Mhania

Archives of Acoustics

2021

Vol. 46, No. 2

237--247

Orthographic-To-Phonetic (O2P) Transcription is the process of learning the relationship between the written word and its phonetic transcription. It is a necessary part of Text-To-Speech (TTS) systems and it plays an important role in handling Out-Of-Vocabulary (OOV) words in Automatic Speech Recognition systems. The O2P is a complex task, because for many languages, the correspondence between the orthography and its phonetic transcription is not completely consistent. Over time, the techniques used to tackle this problem have evolved, from earlier rules based systems to the current more sophisticated machine learning approaches. In this paper, we propose an approach for Arabic O2P Conversion based on a probabilistic method: Conditional Random Fields (CRF). We discuss the results and experiments of this method apply on a pronunciation dictionary of the Most Commonly used Arabic Words, a database that we called (MCAW-Dic). MCAW-Dic contains over 35 000 words in Modern Standard Arabic (MSA) and their pronunciation, a database that we have developed by ourselves assisted by phoneticians and linguists from the University of Tlemcen. The results achieved are very satisfactory and point the way towards future innovations. Indeed, in all our tests, the score was between 11 and 15% error rate on the transcription of phonemes (Phoneme Error Rate). We could improve this result by including a large context, but in this case, we encountered memory limitations and calculation difficulties.

W stronę mowy syntetycznej o naturalnym brzmieniu

Janicki A.

Przegląd Telekomunikacyjny + Wiadomości Telekomunikacyjne

2006

nr 1

13-16

Przedstawiono dwa sposoby poprawy jakości syntezy mowy dla języka polskiego. Zaproponowano metodę rozpoznawania części mowy dla języka polskiego z wykorzystaniem sieci neuronowych. Przedstawiono wyniki weryfikacji działania zaproponowanych metod.

Two methods of improving quality of Polish synthetic speech are presented in the paper. The first one is an enhanced method of controlling duration of phonemes; the second one is use of artificial neural network to model intonation of synthetic phrase. A method of part-of-speech tagging for the Polish language using neural networks is proposed. The results of verification of the proposed methods are presented.