Borrowing Language Resources for Development of Automatic Speech Recognition for Low- and Middle-Density Languages

In this paper we describe an approach that both creates crosslingual acoustic monophone model sets for speech recognition tasks and objectively predicts their performance without target-language speech data or acoustic measurement techniques. This strategy is based on a series of linguistic metrics characterizing the articulatory phonetic and phonological distances of target-language phonemes from source-language phonemes. We term these algorithms the Combined Phonetic and Phonological Crosslingual Distance (CPP-CD) metric and the Combined Phonetic and Phonological Crosslingual Prediction (CPP-CP) metric. The particular motivations for this project are the current unavailability and often prohibitively high production cost of speech databases for many strategically important low- and middle-density languages. First, we describe the CPP-CD approach and compare the performance of CPP-CD-specified models to both native language models and crosslingual models selected by the Bhattacharyya...

• Type: Conference
• Year: 2008
• Where: LREC
• Authors: Lynette Melnar, Chen Liu
• Keywords: Education, LREC 2008, Phonological Crosslingual Distance, Speech Recognition Tasks, Target-language Speech Data