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

Author

Tsujino, Kenji ; Nakashima, Yuta ; Iizuka, Soh ; Isoda, Yoshinori

Author_Institution

Res. Labs., NTT DOCOMO, Inc., Yokosuka, Japan

Volume

2

fYear

2013

fDate

3-6 June 2013

Firstpage

225

Lastpage

228

Abstract

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.

Keywords

mobile computing; natural language processing; personal computing; speech recognition; ASR; SLU system; Shabette Concier; mobile personal assistant; spoken language understanding; statistical automatic speech recognition; voice-based personal assistant application; Data handling; Data storage systems; Engines; Information management; Smart phones; Speech; Speech recognition; big data; natural language processing; speech recognition; spoken language understanding;

fLanguage

English

Publisher

ieee

Conference_Titel

Mobile Data Management (MDM), 2013 IEEE 14th International Conference on

Conference_Location

Milan

Print_ISBN

978-1-4673-6068-5

Type

conf

DOI

10.1109/MDM.2013.98

Filename

6569094