کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
566035 | 875912 | 2008 | 18 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Joint-sequence models for grapheme-to-phoneme conversion Joint-sequence models for grapheme-to-phoneme conversion](/preview/png/566035.png)
Grapheme-to-phoneme conversion is the task of finding the pronunciation of a word given its written form. It has important applications in text-to-speech and speech recognition. Joint-sequence models are a simple and theoretically stringent probabilistic framework that is applicable to this problem. This article provides a self-contained and detailed description of this method. We present a novel estimation algorithm and demonstrate high accuracy on a variety of databases. Moreover, we study the impact of the maximum approximation in training and transcription, the interaction of model size parameters, n-best list generation, confidence measures, and phoneme-to-grapheme conversion. Our software implementation of the method proposed in this work is available under an Open Source license.
Journal: Speech Communication - Volume 50, Issue 5, May 2008, Pages 434–451