DE eng

Search in the Catalogues and Directories

Page: 1 2 3
Hits 41 – 47 of 47

41
Addendum to "What generic statements imply about unmentioned gender groups" ...
Moty, Kelsey. - : Open Science Framework, 2022
BASE
Show details
42
Multiplayer Tangrams study 2.01 : 6-player no-rotation ...
Boyce, Veronica. - : Open Science Framework, 2022
BASE
Show details
43
Encoding inferential evidence for events in language: Evidence from Turkish speaking children ...
Ünal, Ercenur. - : Open Science Framework, 2022
BASE
Show details
44
Emotion, discourse, and linguistic diversity: Emotions in grammar and discourse in northern Australia ...
Languaging Diversity 2021 2021; Ponsonnet, Maïa. - : Underline Science Inc., 2022
BASE
Show details
45
Linguistic Complexity and Planning Effects on Word Duration in Hindi Read Aloud Speech
In: Proceedings of the Society for Computation in Linguistics (2022)
Abstract: Our study investigates the impact of linguistic complexity and planning on word durations in Hindi read aloud speech. Reading aloud involves both comprehension and production processes, and we use measures defined by two influential theories of sentence comprehension, Surprisal Theory and Dependency Locality Theory, to model the time taken to enunciate individual words. We model planning processes using an information-theoretic measure we call FORWARD SURPRISAL, inspired by surprisal theory which has been prominent in recent psycholinguistic work. Forward surprisal aims to capture articulatory planning when readers incorporate parafoveal viewing during reading aloud. Using a Linear Mixed Model containing memory and surprisal costs as predictors of word duration in read aloud speech (parts-of-speech and speakers being intercept terms), we investigate the following hypotheses: 1. High values of linguistic complexity measures (lexical+PCFG surprisal and DLT memory costs) lead to high word durations. 2. High values of forward lexical surprisal tend to induce high word durations. 3. High-frequency words are read aloud faster than low-frequency words. We validate the above hypotheses using data from the TDIL corpus of read aloud speech. Further, using a Generalized Linear Model to predict content and function word labels we show that lexical surprisal measures do not help distinguish between these 2 classes. Thus reading aloud might not involve distinct access strategies for content and function words, unlike spontaneous speech.
Keyword: Applied Linguistics; Cognition and Perception; Cognitive Psychology; Cognitive Science; Comprehension; Computational Linguistics; Hindi; Language Production; Linguistic Complexity; Locality; Parafoveal Processing; Phonetics and Phonology; Planning; Psycholinguistics and Neurolinguistics; Reading; Reading Aloud; Surprisal; Typological Linguistics and Linguistic Diversity
URL: https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1260&context=scil
https://scholarworks.umass.edu/scil/vol5/iss1/11
BASE
Hide details
46
Evaluating Structural Economy Claims in Relative Clause Attachment
In: Proceedings of the Society for Computation in Linguistics (2022)
BASE
Show details
47
The Electrophysiological Correlates of Text Integration and Direct vs. Indirect Articles: A Centralized and Lateralized Examination
In: Theses and Dissertations (Comprehensive) (2022)
BASE
Show details

Page: 1 2 3

Catalogues
0
0
0
0
0
0
0
Bibliographies
0
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
0
0
0
0
Open access documents
47
0
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern