In this paper we present an isolated -word recognition system using first HMM to recognize the underlying sequence of phonemes, then DP and phoneme n -gram matching techniques to determi ne the corresponding nearest idealized phoneme sequences in the dictionary. Our approach is based on the observation that there is almost a one -to-one match between phonemes and letters in the official written...

Phonetic transcriptions contain rich information about language. First, the sequential patterns in phonetic transcripts reveal information about the language’s phonotactics. When combined with lexical information, this can help to grow or correct pronunciation dictionaries and to improve grapheme-to-phoneme prediction. Second, the places where pronunciations deviate from the norm can be equally...

The German language is interspersed wi th words, mostly foreign words, which cannot be converted correctly by German graphemeto-phoneme rules. Almost all of these words belong to the English or French language. In order to convert the whole text correctly, it is necessary to identify the language of each word and then to use the corresponding set of grapheme-to-phoneme rules. The problern of la...

We present a lexicon-based model for segmenting Chinese text into dictionary entries and for providing pronunciations for these words. This approach adopts a matching algorithm combined with several heuristic rules to resolve the ambiguities. It can achieve total accuracy over 95%, which proved to be an effective solution to grapheme-to-phoneme conversion for Mandarin Chinese. Introduction The ...

This paper presents steps in accessing Thai phoneme distribution from large-scale written Thai corpora. The data were from 12 text genres from InterBEST [1], considered the biggest Thai corpora. Each word was transliterated using the grapheme-to-phoneme software [2]. Then, frequency of words, frequency of 81 Thai phonemes in each genre, and the 95% CIs of average occurrences of each phoneme wer...

We show that a good approach for the grapheme-to-phoneme conversion of Dutch proper names (e.g. person names, toponyms, etc), is to use a cascade of a general purpose grapheme-to-phoneme (G2P) converter and a special purpose phoneme-to-phoneme (P2P) converter. The G2P produces an initial transcription that is then transformed by the P2P. The P2P is automatically trained on reference transcripti...

We propose a new approach for performing phonetic transcription of text that utilizes automatic speech recognition (ASR) to help traditional grapheme-to-phoneme (G2P) techniques. This approach was applied to transcribe Chinese text into Taiwanese phonetic symbols. By augmenting the text with speech and using automatic speech recognition with a sausage searching net constructed from multiple pro...