Paper Info
Title
A New Approach to Syllabification of Words in Gujarati.
Abstract
This paper presents a statistical approach for automatic syllabification of words in Gujarati. Gujarati is a resource poor language and hardly any work for its syllabification has been reported, to the best our knowledge. Specifically, lack of enough training data makes this task difficult to perform. A training corpus of 14 thousand Gujarati words is built and a new approach to syllabification in Gujarati is tested on it. The maximum word and syllable level accuracies achieved are 91.89﾿% and 98.02﾿% respectively.
Year
DOI
Venue
2015
10.1007/978-3-319-26832-3_59
MIKE
Field
DocType
Citations 
Gujarati,Training set,Computer science,Syllabification,Speech recognition,Natural language processing,Artificial intelligence,Syllable,Poor language
Conference
0
PageRank 
References 
Authors
0.34
5
3
Name
Order
Citations
PageRank
Harsh Trivedi143.51
Aanal Patel200.34
Prasenjit Majumder317325.15