Speech Recognition and Spoken Language Understanding for Mobile Personal Assistants: a Case Study of "Shabette Concier"

被引：4
|
作者：
Tsujino, Kosuke [1 ]
Nakashima, Yusuke [1 ]
Iizuka, Shinya [1 ]
Isoda, Yoshinori [2 ]
机构：
[1] NTT DOCOMO Inc, Res Labs, Yokosuka, Kanagawa, Japan
[2] NTT DOCOMO Inc, Serv & Solut Dev Dept, Yokosuka, Kanagawa, Japan
来源：
2013 IEEE 14TH INTERNATIONAL CONFERENCE ON MOBILE DATA MANAGEMENT (MDM 2013), VOL 2 | 2013年
关键词：
speech recognition; natural language processing; spoken language understanding; big data;
D O I：
10.1109/MDM.2013.98
中图分类号：
TN [电子技术、通信技术];
学科分类号：
0809 ;
摘要：
Recent success of mobile personal assistants deeply relies on the advancement in statistical automatic speech recognition (ASR) and spoken language understanding (SLU) technologies. This article describes practical design of ASR and SLU systems for "Shabette Concier", a voice-based personal assistant application commercially released by NTT docomo in Japan in March 2012. Utilization of a large amount of field speech data gathered from the actual service is focused and the potential of big data is discussed.
引用
收藏
页码：225 / 228
页数：4
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