Measuring unsupervised acoustic clustering through phoneme pair merge-and-split tests

Autor:	John Kominek, Alan W. Black
Rok vydání:	2005
Předmět:	symbols.namesake Computer science business.industry Speech recognition Gaussian k-means clustering Canopy clustering algorithm symbols Pattern recognition Artificial intelligence Cluster analysis business Merge (linguistics)
Zdroj:	INTERSPEECH
DOI:	10.21437/interspeech.2005-198
Popis:	Subphonetic discovery through segmental clustering is a central step in building a corpus-based synthesizer. To help decide what clustering algorithm to use we employed mergeand-split tests on English fricatives. Compared to reference of 2%, Gaussian EM achieved a misclassification rate of 6%, Kmeans 10%, while predictive CART trees performed poorly.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::09a36c14fcf7142a7e8909f8bd6162bb https://doi.org/10.21437/interspeech.2005-198 Zobrazit plný text záznamu