Rule-based grapheme-to-phonem
نویسندگان
چکیده
This paper describes a trainable method for generating letter to sound rules for the Greek language, for producing the pronunciation of out-of-vocabulary words. Several approaches have been adopted over the years for graphemeto-phoneme conversion, such as hand-seeded rules, finite state transducers, neural networks, HMMs etc, nevertheless it has been proved that the most reliable method is a rule-based one. Our approach is based on a semi-automatically pretranscribed lexicon, from which we derived rules for automatic transcription. The efficiency and robustness of our method are proved by experiments on out-of-vocabulary words which resulted in over than 98% accuracy on a wordbase criterion.
منابع مشابه
Rule-based Korean Grapheme to Phoneme Conversion Using Sound Patterns
Grapheme-to-phoneme conversion plays an important role in text-to-speech applications and other fields of computational linguistics. Although Korean uses a phonemic writing system, it must have a grapheme-to-phoneme conversion for speech synthesis because Korean writing system does not always reflect its actual pronunciations. This paper describes a grapheme-to-phoneme conversion method based o...
متن کاملModified Grapheme Encoding and Phonemic Rule to Improve PNNR-Based Indonesian G2P
A grapheme-to-phoneme conversion (G2P) is very important in both speech recognition and synthesis. The existing Indonesian G2P based on pseudo nearest neighbour rule (PNNR) has two drawbacks: the grapheme encoding does not adapt all Indonesian phonemic rules and the PNNR should select a best phoneme from all possible conversions even though they can be filtered by some phonemic rules. In this p...
متن کاملPronunciation of P with a Joint N-gram Model Grapheme-to-phonem
Pronunciation of proper names is known to be a difficult problem, but one of great practical importance for both speech synthesis and speech recognition. Recently a few data-driven grapheme-to-phoneme conversion techniques have been proposed to tackle this problem. In this paper we apply the joint n-gram model for bi-directional grapheme-to-phoneme conversion, which has already been shown to ac...
متن کاملDecision Tree Learning for Automatic Grapheme to Phoneme Conversion for Tamil N.Udhyakumar, C.S.Kumar, R.Srinivasan and R.Swaminathan
This paper describes a novel approach for grapheme to phoneme conversion using decision tree learning technique. The proposed approach, unlike the rule based approach, can generate rules spanning wider context and thus give better accuracy for the conversion.
متن کاملInferring Hierarchical Pronunciation Rules from a Phonetic Dictionary
This work presents a new phonetic transcription system based on a tree of hierarchical pronunciation rules expressed as context-specific grapheme-phoneme correspondences. The tree is automatically inferred from a phonetic dictionary by incrementally analyzing deeper context levels, eventually representing a minimum set of exhaustive rules that pronounce without errors all the words in the train...
متن کامل