@inproceedings{KanokpharaGeumannCarsonBerndsen2016, author = {Supphanat Kanokphara and Anja Geumann and Julie Carson-Berndsen}, title = {Accessing Language Specific Linguistic Information for Triphone Model Generation: Feature Tables in a Speech Recognition System}, series = {Proceedings of the 2nd Language \& Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics, April 21-23, Poznań, Poland (L\&TC'05)}, editor = {Zygmunt Vetulani}, publisher = {Wydawnictwo Poznańskie}, address = {Poznań}, isbn = {83-7177-341-2}, url = {https://nbn-resolving.org/urn:nbn:de:bsz:mh39-57064}, pages = {7 -- 10}, year = {2016}, abstract = {This paper is concerned with a novel methodology for generating phonetic questions used in tree-based state tying for speech recognition. In order to implement a speech recognition system, language-dependent knowledge which goes beyond annotated material is usually required. The approach presented here generates phonetic questions for decision trees are based on a feature table that summarizes the articulatory characteristics of each sound. On the one hand, this method allows better language-specific triphone models to be defined given only a feature-table as linguistic input. On the other hand, the feature-table approach facilitates efficient definition of triphone models for other languages since again only a feature table for this language is required. The approach is exemplified with speech recognition systems for English and Thai.}, language = {en} }