Segmenting into Adequate Units for Automatic Recognition of Emotion-Related Episodes: A Speech-Based Approach. (18th March 2010)
- Record Type:
- Journal Article
- Title:
- Segmenting into Adequate Units for Automatic Recognition of Emotion-Related Episodes: A Speech-Based Approach. (18th March 2010)
- Main Title:
- Segmenting into Adequate Units for Automatic Recognition of Emotion-Related Episodes: A Speech-Based Approach
- Authors:
- Batliner, Anton
Seppi, Dino
Steidl, Stefan
Schuller, Björn - Other Names:
- Andre Elisabeth Academic Editor.
- Abstract:
- Abstract : We deal with the topic of segmenting emotion-related (emotional/affective) episodes into adequate units for analysis and automatic processing/classification—a topic that has not been addressed adequately so far. We concentrate on speech and illustrate promising approaches by using a database with children's emotional speech. We argue in favour of the word as basic unit and map sequences of words on both syntactic and ''emotionally consistent" chunks and report classification performances for an exhaustive modelling of our data by mapping word-based paralinguistic emotion labels onto three classes representing valence (positive, neutral, negative), and onto a fourth rest (garbage) class.
- Is Part Of:
- Advances in human-computer interaction. Volume 2010(2010)
- Journal:
- Advances in human-computer interaction
- Issue:
- Volume 2010(2010)
- Issue Display:
- Volume 2010, Issue 2010 (2010)
- Year:
- 2010
- Volume:
- 2010
- Issue:
- 2010
- Issue Sort Value:
- 2010-2010-2010-0000
- Page Start:
- Page End:
- Publication Date:
- 2010-03-18
- Subjects:
- Human-computer interaction -- Periodicals
Human-computer interaction
Periodicals
Electronic journals
004.019 - Journal URLs:
- http://bibpurl.oclc.org/web/50279 ↗
https://www.hindawi.com/journals/ahci/ ↗ - DOI:
- 10.1155/2010/782802 ↗
- Languages:
- English
- ISSNs:
- 1687-5893
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 10279.xml