Accession Number:

AD1038524

Title:

Machine Translation Based Data Augmentation for Cantonese Keyword Spotting (Author's Manuscript)

Descriptive Note:

Conference Paper

Corporate Author:

LIMSI CNRS, Spoken Language Processing Group Orsay Cedex France

Personal Author(s):

• Huang, Guangpu
• Gorin,Arseniy
• Gauvain,Jean-Luc
• Lamel,Lori

Report Date:

2016-05-19

Pagination or Media Count:

5.0

Abstract:

This paper presents a method to improve a language model for a limited-resourced language using statistical machine translation from a related language to generate data for the target language. In this work, the machine translation model is trained on a corpus of parallel Mandarin-Cantonese subtitles and used to translate a large set of Mandarin conversational telephone transcripts to Cantonese, which has limited resources. The translated transcripts are used to train a more robust language model for speech recognition and for keyword search in Cantonese conversational telephone speech. This method enables the keyword search system to detect 1.5 times more out-of-vocabulary words, and achieve 1.7 absolute improvement on actual term-weighted value.

Descriptors:

• automated speech recognition
• artificial neural networks
• machine translation
• detection
• translations
• dictionaries
• training
• recognition
• language
• vocabulary
• artificial intelligence software
• computational linguistics
• automatic

Subject Categories:

• Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE