Automatic Affect Recognition Using Natural Language Processing Techniques and Manually Built Affect Lexicon

Young Hwan CHO; Kong Joo LEE

doi:10.1093/ietisy/e89-d.12.2964

Automatic Affect Recognition Using Natural Language Processing Techniques and Manually Built Affect Lexicon

Young Hwan CHO, Kong Joo LEE

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In this paper, we present preliminary work on recognizing affect from a Korean textual document by using a manually built affect lexicon and adopting natural language processing tools. A manually built affect lexicon is constructed in order to be able to detect various emotional expressions, and its entries consist of emotion vectors. The natural language processing tools analyze an input document to enhance the accuracy of our affect recognizer. The performance of our affect recognizer is evaluated through automatic classification of song lyrics according to moods.

Publication: IEICE TRANSACTIONS on Information Vol.E89-D No.12 pp.2964-2971

Publication Date: 2006/12/01

Publicized

Online ISSN: 1745-1361

DOI: 10.1093/ietisy/e89-d.12.2964

Type of Manuscript: PAPER

Category: Natural Language Processing

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Young Hwan CHO, Kong Joo LEE, "Automatic Affect Recognition Using Natural Language Processing Techniques and Manually Built Affect Lexicon" in IEICE TRANSACTIONS on Information, vol. E89-D, no. 12, pp. 2964-2971, December 2006, doi: 10.1093/ietisy/e89-d.12.2964.
Abstract: In this paper, we present preliminary work on recognizing affect from a Korean textual document by using a manually built affect lexicon and adopting natural language processing tools. A manually built affect lexicon is constructed in order to be able to detect various emotional expressions, and its entries consist of emotion vectors. The natural language processing tools analyze an input document to enhance the accuracy of our affect recognizer. The performance of our affect recognizer is evaluated through automatic classification of song lyrics according to moods.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e89-d.12.2964/_p

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@ARTICLE{e89-d_12_2964,
author={Young Hwan CHO, Kong Joo LEE, },
journal={IEICE TRANSACTIONS on Information},
title={Automatic Affect Recognition Using Natural Language Processing Techniques and Manually Built Affect Lexicon},
year={2006},
volume={E89-D},
number={12},
pages={2964-2971},
abstract={In this paper, we present preliminary work on recognizing affect from a Korean textual document by using a manually built affect lexicon and adopting natural language processing tools. A manually built affect lexicon is constructed in order to be able to detect various emotional expressions, and its entries consist of emotion vectors. The natural language processing tools analyze an input document to enhance the accuracy of our affect recognizer. The performance of our affect recognizer is evaluated through automatic classification of song lyrics according to moods.},
keywords={},
doi={10.1093/ietisy/e89-d.12.2964},
ISSN={1745-1361},
month={December},}

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TY - JOUR
TI - Automatic Affect Recognition Using Natural Language Processing Techniques and Manually Built Affect Lexicon
T2 - IEICE TRANSACTIONS on Information
SP - 2964
EP - 2971
AU - Young Hwan CHO
AU - Kong Joo LEE
PY - 2006
DO - 10.1093/ietisy/e89-d.12.2964
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E89-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2006
AB - In this paper, we present preliminary work on recognizing affect from a Korean textual document by using a manually built affect lexicon and adopting natural language processing tools. A manually built affect lexicon is constructed in order to be able to detect various emotional expressions, and its entries consist of emotion vectors. The natural language processing tools analyze an input document to enhance the accuracy of our affect recognizer. The performance of our affect recognizer is evaluated through automatic classification of song lyrics according to moods.
ER -