Paper Info
Title
Towards Multilingual Conversations in the Medical Domain: Development of Multilingual Medical Data and A Network-based ASR System.
Abstract
This paper outlines the recent development on multilingual medical data and multilingual speech recognition system for network-based speech-to-speech translation in the medical domain. The overall speech-to-speech translation (S2ST) system was designed to translate spoken utterances from a given source language into a target language in order to facilitate multilingual conversations and reduce the problems caused by language barriers in medical situations. Our final system utilizes a weighted finite-state transducers with n-gram language models. Currently, the system successfully covers three languages: Japanese, English, and Chinese. The difficulties involved in connecting Japanese, English and Chinese speech recognition systems through Web servers will be discussed, and the experimental results in simulated medical conversation will also be presented.
Year
Venue
Keywords
2014
LREC 2014 - NINTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
multilingual data,speech recognition,medical domain
Field
DocType
Citations 
Language barrier,Conversation,Computer science,Artificial intelligence,Natural language processing,Language model,Web server
Conference
1
PageRank 
References 
Authors
0.39
12
8
Name
Order
Citations
PageRank
Sakriani Sakti125765.02
Keigo Kubo262.34
Sho Matsumiya310.73
Graham Neubig4989130.31
Tomoki Toda51874167.18
Satoshi Nakamura61099194.59
Fumihiro Adachi7132.87
Ryosuke Isotani83810.60