Group sparse CNNs for question classification with answer sets
Mingbo Ma, Liang Huang, et al.
ACL 2017
In this paper, we describe the IBM MASTOR systems which handle spontaneous free-form speech-to-speech translation on both laptop and hand-held PDAs. Challenges include speech recognition and machine translation in adverse environments, lack of data and linguistic resources for under-studied languages, and the need to rapidly develop capabilities for new languages. Importantly, the code and models must fit within the limited memory and computational resources of hand-held devices. We describe our approaches, experience, and success in building working free-form S2S systems that can handle two language pairs (including a low-resource language).
Mingbo Ma, Liang Huang, et al.
ACL 2017
Bowen Zhou, Bing Xiang, et al.
SSST 2008
Mo Yu, Wenpeng Yin, et al.
ACL 2017
Jia Cui, Yonggang Deng, et al.
ASRU 2009