You tube movie reviews: Sentiment analysis in an audio-visual context

Martin Wollmer; Felix Weninger; Tobias Knaup; Bjorn Schuller; Congkai Sun; Kenji Sagae; Louis Philippe Morency

doi:10.1109/MIS.2013.34

You tube movie reviews: Sentiment analysis in an audio-visual context

Martin Wollmer
, Felix Weninger
, Tobias Knaup
, Bjorn Schuller
, Congkai Sun
, Kenji Sagae
, Louis Philippe Morency

Chair of Health Informatics

Research output: Contribution to journal › Article › peer-review

361 Scopus citations

Abstract

This work focuses on automatically analyzing a speaker's sentiment in online videos containing movie reviews. In addition to textual information, this approach considers adding audio features as typically used in speech-based emotion recognition as well as video features encoding valuable valence information conveyed by the speaker. Experimental results indicate that training on written movie reviews is a promising alternative to exclusively using (spoken) in-domain data for building a system that analyzes spoken movie review videos, and that language-independent audio-visual analysis can compete with linguistic analysis.

Original language	English
Article number	6487473
Pages (from-to)	46-53
Number of pages	8
Journal	IEEE Intelligent Systems
Volume	28
Issue number	3
DOIs	https://doi.org/10.1109/MIS.2013.34
State	Published - 2013

Keywords

affective computing
audio-visual pattern recognition
intelligent systems
linguistic analysis
sentiment analysis

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10.1109/MIS.2013.34

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title = "You tube movie reviews: Sentiment analysis in an audio-visual context",

abstract = "This work focuses on automatically analyzing a speaker's sentiment in online videos containing movie reviews. In addition to textual information, this approach considers adding audio features as typically used in speech-based emotion recognition as well as video features encoding valuable valence information conveyed by the speaker. Experimental results indicate that training on written movie reviews is a promising alternative to exclusively using (spoken) in-domain data for building a system that analyzes spoken movie review videos, and that language-independent audio-visual analysis can compete with linguistic analysis.",

keywords = "affective computing, audio-visual pattern recognition, intelligent systems, linguistic analysis, sentiment analysis",

author = "Martin Wollmer and Felix Weninger and Tobias Knaup and Bjorn Schuller and Congkai Sun and Kenji Sagae and Morency, \{Louis Philippe\}",

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AU - Knaup, Tobias

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AU - Sun, Congkai

AU - Sagae, Kenji

AU - Morency, Louis Philippe

PY - 2013

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AB - This work focuses on automatically analyzing a speaker's sentiment in online videos containing movie reviews. In addition to textual information, this approach considers adding audio features as typically used in speech-based emotion recognition as well as video features encoding valuable valence information conveyed by the speaker. Experimental results indicate that training on written movie reviews is a promising alternative to exclusively using (spoken) in-domain data for building a system that analyzes spoken movie review videos, and that language-independent audio-visual analysis can compete with linguistic analysis.

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KW - audio-visual pattern recognition

KW - intelligent systems

KW - linguistic analysis

KW - sentiment analysis

UR - https://www.scopus.com/pages/publications/84884134833

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ER -

You tube movie reviews: Sentiment analysis in an audio-visual context

Abstract

Keywords

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