TY - JOUR
T1 - Team ELISA system for DARPA LORELEI speech evaluation 2016
AU - Papadopoulos, Pavlos
AU - Travadi, Ruchir
AU - Vaz, Colin
AU - Malandrakis, Nikolaos
AU - Hermjakob, Ulf
AU - Pourdamghani, Nima
AU - Pust, Michael
AU - Zhang, Boliang
AU - Pan, Xiaoman
AU - Lu, Di
AU - Lin, Ying
AU - Glembek, Ondřej
AU - Baskar, Murali Karthick
AU - Karafiát, Martin
AU - Burget, Lukáš
AU - Hasegawa-Johnson, Mark
AU - Ji, Heng
AU - May, Jonathan
AU - Knight, Kevin
AU - Narayanan, Shrikanth
N1 - Publisher Copyright:
Copyright © 2017 ISCA.
PY - 2017
Y1 - 2017
N2 - In this paper, we describe the system designed and developed by team ELISA for DARPA's LORELEI (Low Resource Languages for Emergent Incidents) pilot speech evaluation. The goal of the LORELEI program is to guide rapid resource deployment for humanitarian relief (e.g. for natural disasters), with a focus on "low-resource" language locations, where the cost of developing technologies for automated human language tools can be prohibitive both in monetary terms and timewise. In this phase of the program, the speech evaluation consisted of three separate tasks: detecting presence of an incident, classifying incident type, and classifying incident type along with identifying the location where it occurs. The performance metric was area under curve of precision-recall curves. Team ELISA competed against five other teams and won all the subtasks.
AB - In this paper, we describe the system designed and developed by team ELISA for DARPA's LORELEI (Low Resource Languages for Emergent Incidents) pilot speech evaluation. The goal of the LORELEI program is to guide rapid resource deployment for humanitarian relief (e.g. for natural disasters), with a focus on "low-resource" language locations, where the cost of developing technologies for automated human language tools can be prohibitive both in monetary terms and timewise. In this phase of the program, the speech evaluation consisted of three separate tasks: detecting presence of an incident, classifying incident type, and classifying incident type along with identifying the location where it occurs. The performance metric was area under curve of precision-recall curves. Team ELISA competed against five other teams and won all the subtasks.
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U2 - 10.21437/Interspeech.2017-180
DO - 10.21437/Interspeech.2017-180
M3 - Conference article
AN - SCOPUS:85039161955
SN - 2308-457X
VL - 2017-August
SP - 2053
EP - 2057
JO - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
JF - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
T2 - 18th Annual Conference of the International Speech Communication Association, INTERSPEECH 2017
Y2 - 20 August 2017 through 24 August 2017
ER -