Papers with production servers
Improving homograph disambiguation with supervised machine learning (L18-1)
Copied to clipboard
| Challenge: | a new system for text-to-speech synthesis uses rule-based homograph disambiguation . a simple application of machine learning produces significant improvements in homograph ambiguity . |
| Approach: | They propose a rule-based homograph disambiguation system for text-to-speech synthesis at Google . they compare it to a new system which performs disambiguations using classifiers trained on labeled data . |
| Outcome: | The proposed system is more accurate than hand-written rules or machine learning alone. |