Abstract
| Original language | Undefined |
|---|---|
| Title of host publication | First International IEEE Workshop on Spoken Language Technology SLT 2006 |
| Editors | B. Raorke |
| Place of Publication | Palm Beach |
| Publisher | IEEE Computer Society |
| Pages | 70-73 |
| Number of pages | 4 |
| ISBN (Print) | 1-4244-0873-3 |
| DOIs | |
| Publication status | Published - Dec 2006 |
Publication series
| Name | |
|---|---|
| Publisher | IEEE Computer Society |
| Number | 10 |
Keywords
- EC Grant Agreement nr.: FP6/506811
- EWI-9501
- IR-67003
- METIS-237662
- HMI-CI: Computational Intelligence
Cite this
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Dialogue-act tagging using smart feature selection: results on multiple corpora. / Verbree, Daan; Rienks, R.J.; Heylen, Dirk K.J.
First International IEEE Workshop on Spoken Language Technology SLT 2006. ed. / B. Raorke. Palm Beach : IEEE Computer Society, 2006. p. 70-73.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - Dialogue-act tagging using smart feature selection: results on multiple corpora
AU - Verbree, Daan
AU - Rienks, R.J.
AU - Heylen, Dirk K.J.
PY - 2006/12
Y1 - 2006/12
N2 - This paper presents an overview of our on-going work on dialogueact classification. Results are presented on the ICSI, Switchboard, and on a selection of the AMI corpus, setting a baseline for forthcoming research. For these corpora the best accuracy scores obtained are 89.27%, 65.68% and 59.76%, respectively. We introduce a smart compression technique for feature selection and compare the performance from a subset of the AMI transcriptions with AMI-ASR output for the same subset.
AB - This paper presents an overview of our on-going work on dialogueact classification. Results are presented on the ICSI, Switchboard, and on a selection of the AMI corpus, setting a baseline for forthcoming research. For these corpora the best accuracy scores obtained are 89.27%, 65.68% and 59.76%, respectively. We introduce a smart compression technique for feature selection and compare the performance from a subset of the AMI transcriptions with AMI-ASR output for the same subset.
KW - EC Grant Agreement nr.: FP6/506811
KW - EWI-9501
KW - IR-67003
KW - METIS-237662
KW - HMI-CI: Computational Intelligence
U2 - 10.1109/SLT.2006.326819
DO - 10.1109/SLT.2006.326819
M3 - Conference contribution
SN - 1-4244-0873-3
SP - 70
EP - 73
BT - First International IEEE Workshop on Spoken Language Technology SLT 2006
A2 - Raorke, B.
PB - IEEE Computer Society
CY - Palm Beach
ER -