Publication:

Measuring Encoding Efficiency in Swedish and English Language Learner Speech Production

Date

Date

Date
2017
Conference or Workshop Item
Published version

Citations

Citation copied

Grigonyte, G., & Schneider, G. (2017). Measuring Encoding Efficiency in Swedish and English Language Learner Speech Production. 1779–1783. https://doi.org/10.21437/Interspeech.2017-337

Abstract

Abstract

Abstract

We use n-gram language models to investigate how far language approximates an optimal code for human communication in terms of Information Theory, and what differences there are between Learner proficiency levels. Although the language of lower level learners is simpler, it is less optimal in terms of information theory, and as a consequence more difficult to process.

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54 since deposited on 2018-01-17
Acq. date: 2025-11-09

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187 since deposited on 2018-01-17
Acq. date: 2025-11-09

Citations

Additional indexing

Creators (Authors)

  • Grigonyte, Gintare
    affiliation.icon.alt
  • Schneider, Gerold
    affiliation.icon.alt

Event Title

Event Title

Event Title
Interspeech 2017

Event Location

Event Location

Event Location
Stockholm

Event Start Date

Event Start Date

Event Start Date
2017-08-19

Event End Date

Event End Date

Event End Date
2017-08-24

Publisher

Publisher

Publisher

Page Range

Page Range

Page Range
1779

Page end

Page end

Page end
1783

Item Type

Item Type

Item Type
Conference or Workshop Item

Dewey Decimal Classifikation

Dewey Decimal Classifikation

Dewey Decimal Classifikation

Language

Language

Language
English

Date available

Date available

Date available
2018-01-17

OA Status

OA Status

OA Status
Green

Free Access at

Free Access at

Free Access at
DOI

Metrics

Downloads

54 since deposited on 2018-01-17
Acq. date: 2025-11-09

Views

187 since deposited on 2018-01-17
Acq. date: 2025-11-09

Citations

Citations

Citation copied

Grigonyte, G., & Schneider, G. (2017). Measuring Encoding Efficiency in Swedish and English Language Learner Speech Production. 1779–1783. https://doi.org/10.21437/Interspeech.2017-337

Green Open Access
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Files

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