Search: onr:"swepub:oai:DiVA.org:su-158890" >
The language of sme...
The language of smell : Connecting linguistic and psychophysical properties of odor descriptors
-
- Iatropoulos, Georgios (author)
- Stockholms universitet,Perception och psykofysik
-
- Herman, Pawel, 1979- (author)
- KTH,Beräkningsvetenskap och beräkningsteknik (CST),Computational Brain Science Laboratory, KTH
-
- Lansner, Anders, Professor (author)
- KTH,Beräkningsvetenskap och beräkningsteknik (CST),Computational Brain Science Laboratory, KTH
-
show more...
-
- Karlgren, Jussi (author)
- KTH,Teoretisk datalogi, TCS,Gavagai, Slussplan 9, Stockholm, Sweden,Human Language Technology Group,
-
- Larsson, Maria (author)
- Stockholms universitet,Perception och psykofysik
-
- Olofsson, Jonas K. (author)
- Stockholms universitet,Perception och psykofysik
-
show less...
-
(creator_code:org_t)
- Elsevier BV, 2018
- 2018
- English.
-
In: Cognition. - : Elsevier BV. - 0010-0277 .- 1873-7838. ; 178, s. 37-49
- Related links:
-
https://psyarxiv.com...
-
show more...
-
https://urn.kb.se/re...
-
https://doi.org/10.1...
-
https://urn.kb.se/re...
-
show less...
Abstract
Subject headings
Close
- The olfactory sense is a particularly challenging domain for cognitive science investigations of perception, memory, and language. Although many studies show that odors often are difficult to describe verbally, little is known about the associations between olfactory percepts and the words that describe them. Quantitative models of how odor experiences are described in natural language are therefore needed to understand how odors are perceived and communicated. In this study, we develop a computational method to characterize the olfaction related semantic content of words in a large text corpus of internet sites in English. We introduce two new metrics: olfactory association index (OAI, how strongly a word is associated with olfaction) and olfactory specificity index (OSI, how specific a word is in its description of odors). We validate the OAI and OSI metrics using psychophysical datasets by showing that terms with high OM have high ratings of perceived olfactory association and are used to describe highly familiar odors. In contrast, terms with high OSI have high inter-individual consistency in how they are applied to odors. Finally, we analyze Dravnieks's (1985) dataset of odor ratings in terms of OAI and OSI. This analysis reveals that terms that are used broadly (applied often but with moderate ratings) tend to be olfaction-unrelated and abstract (e.g., heavy or light; low OAI and low OSI) while descriptors that are used selectively (applied seldom but with high ratings) tend to be olfaction-related (e.g., vanilla or licorice; high OM). Thus, OAI and OSI provide behaviorally meaningful information about olfactory language. These statistical tools are useful for future studies of olfactory perception and cognition, and might help integrate research on odor perception, neuroimaging, and corpus-based linguistic models of semantic organization.
Subject headings
- SAMHÄLLSVETENSKAP -- Psykologi (hsv//swe)
- SOCIAL SCIENCES -- Psychology (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Språkteknologi (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Language Technology (hsv//eng)
Keyword
- odour naming
- odour identification
- sensory lexicon
- sensory-semantic integration
- distributional semantics
- computational linguistics
- Psychology
- psykologi
Publication and Content Type
- ref (subject category)
- art (subject category)
Find in a library
-
Cognition
(Search for host publication in LIBRIS)
To the university's database