Merging of native and non-native speech for low-resource accented ASR

• Main Authors: Samson Juan, Sarah, Besacier, Laurent, Lecouteux, Benjamin, Tien-Ping, Tan
• Format: E-Article
• Language: English
• Published: Springer Verlag 2015
• Subjects: T Technology (General)
• Online Access: http://ir.unimas.my/id/eprint/12098/1/No%2035%20%28abstrak%29.pdf; http://ir.unimas.my/id/eprint/12098/; http://www.scopus.com/inward/record.url?eid=2-s2.0-84952362047&partnerID=40&md5=6bc512988afc29cd7ca4af16a836f0b3

This paper presents our recent study on low-resource automatic speech recognition (ASR) system with accented speech. We propose multi-accent Subspace Gaussian Mixture Models (SGMM) and accent-specific Deep Neural Networks (DNN) for improving non-native ASR performance. In the SGMM framework, we pres...