Grapheme-to-phoneme transcription rules for Spanish, with application to automatic speech recognition and synthesis. Bonaventura, P.; Giuliani, F.; Garrido, J. M.; and Ortín, I. In CVIR 1998. Workshop on Content Visualization and Intermedia Representations (COLING-ACL 1998. 36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics), pages 33-39, Montreal, Quebec, Canada.
Grapheme-to-phoneme transcription rules for Spanish, with application to automatic speech recognition and synthesis [pdf]Paper  abstract   bibtex   
Large phonetic corpora including both standard and variant transcriptions are available for many languages. However, applications requiring the use of dynamic vocabularies make necessary to transcribe words not present in the dictionary. Also, additional alternative pronunciations to standard forms have shown to improve recognition accuracy. Therefore, new techniques to automatically generate variants in pronunciations have been investigated and proven to be very effective. However, rule-based systems still remain useful to generate standard transcriptions not previously available or to build new corpora, oriented chiefly to synthesis applications. The present paper describes a letter-to-phone conversion system for Spanish designed to supply transcriptions to the flexible vocabulary speech recogniser and to the synthesiser, both developed at CSELT (Centro Studi e Laboratori relecomunicazioni), Turin, Italy. Different sets of rules are designed for the two applications. Symbols inventories also differ, although the IPA alphabet is the reference system for both. Rules have been written in ANSI C and implemented on DOS and Windows 95 and can be selectively applied. Two speech corpora have been transcribed by means of these grapheme-to-phoneme conversion rules: a) the SpeechDat Spanish corpus which includes 4444 words extracted from the phonetically balanced sentences of the database b) a corpus designed to train an automatic aligner to segment units for synthesis, composed of 303 sentences (3240 words) and 338 isolated words; rule-based transcriptions of this corpus were manually corrected. The phonetic forms obtained by the rules matched satisfactorily the reference transcriptions: most mistakes on the first corpus were caused by the presence of secondary stresses in the SpeechDat transcriptions, which were not assigned by the rules, whereas errors on the synthesis corpus appeared mostly on hiatuses and on words of foreign origin. Further developments oriented to recognition can imply addition of rules to account for Latin American pronunciations (especially Mexican, Argentinian and Paraguayan); for synthesis, on the other hand, rules to represent coarticulatory phenomena at word boundaries can be implemented, in order to transcribe whole sentences.
@inproceedings{bonaventura_grapheme--phoneme_1998,
	Address = {Montreal, Quebec, Canada},
	Author = {Bonaventura, Patrizia and Giuliani, Fabio and Garrido, Juan María and Ortín, Isabel},
	Booktitle = {CVIR 1998. Workshop on Content Visualization and Intermedia Representations (COLING-ACL 1998. 36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics)},
	Date = {1998},
	Date-Modified = {2016-09-24 18:55:59 +0000},
	File = {Attachment:files/1369/Bonaventura et al. - 1998 - Grapheme-to-phoneme transcription rules for Spanish, with application to automatic speech recognition and sy.pdf:application/pdf},
	Keywords = {automatic phonetic transcription, phonetics, segmental transcription, Spanish, transcription},
	Pages = {33-39},
	Title = {Grapheme-to-phoneme transcription rules for Spanish, with application to automatic speech recognition and synthesis},
	Url = {http://acl.ldc.upenn.edu/W/W98/W98-0804.pdf},
	Abstract = {Large phonetic corpora including both standard and variant transcriptions are available for many languages. However, applications requiring the use of dynamic vocabularies make necessary to transcribe words not present in the dictionary. Also, additional alternative pronunciations to standard forms have shown to improve recognition accuracy. Therefore, new techniques to automatically generate variants in pronunciations have been investigated and proven to be very effective. However, rule-based systems still remain useful to generate standard transcriptions not previously available or to build new corpora, oriented chiefly to synthesis applications. The present paper describes a letter-to-phone conversion system for Spanish designed to supply transcriptions to the flexible vocabulary speech recogniser and to the synthesiser, both developed at CSELT (Centro Studi e Laboratori relecomunicazioni), Turin, Italy. Different sets of rules are designed for the two applications. Symbols inventories also differ, although the IPA alphabet is the reference system for both. Rules have been written in ANSI C and implemented on DOS and Windows 95 and can be selectively applied. Two speech corpora have been transcribed by means of these grapheme-to-phoneme conversion rules: a) the SpeechDat Spanish corpus which includes 4444 words extracted from the phonetically balanced sentences of the database b) a corpus designed to train an automatic aligner to segment units for synthesis, composed of 303 sentences (3240 words) and 338 isolated words; rule-based transcriptions of this corpus were manually corrected. The phonetic forms obtained by the rules matched satisfactorily the reference transcriptions: most mistakes on the first corpus were caused by the presence of secondary stresses in the SpeechDat transcriptions, which were not assigned by the rules, whereas errors on the synthesis corpus appeared mostly on hiatuses and on words of foreign origin. Further developments oriented to recognition can imply addition of rules to account for Latin American pronunciations (especially Mexican, Argentinian and Paraguayan); for synthesis, on the other hand, rules to represent coarticulatory phenomena at word boundaries can be implemented, in order to transcribe whole sentences.},
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