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1
Lexical Emphasis Detection in Spoken French using F-BANKs and neural networks
In: SLSP 2017: Statistical Language and Speech Processing ; International Conference on Statistical Language and Speech Processing (SLSP 2017) ; https://hal.archives-ouvertes.fr/hal-02559768 ; International Conference on Statistical Language and Speech Processing (SLSP 2017), Oct 2017, Le Mans, France. pp.241-249 (2017)
Abstract: International audience ; Expressiveness and non-verbal information in speech are active research topics in speech processing. In this work, we are interested in detecting emphasis at word-level as a mean to identify what are the focus words in a given utterance. We compare several machine learning techniques (Linear Discriminant Analysis, Support Vector Machines, Neural Networks) for this task carried out on SIWIS, a French speech synthesis database. Our approach consists first in aligning the spoken words to the speech signal and second to feed classifier with filter bank coefficients in order to take a binary decision at word-level: neutral/emphasized. Evaluation results show that a three-layer neural network performed best with a 93% accuracy.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; Emphasized content recognition; Non verbal information in speech; SIWIS French speech synthesis database
URL: https://hal.archives-ouvertes.fr/hal-02559768
https://hal.archives-ouvertes.fr/hal-02559768/document
https://hal.archives-ouvertes.fr/hal-02559768/file/Heba_22280.pdf
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2
Взаимодействие Вербальных И Невербальных Средств Коммуникации В Китайской Культуре ...
Лю Юйин; И.А. Быкова. - : Zenodo, 2017
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Взаимодействие Вербальных И Невербальных Средств Коммуникации В Китайской Культуре ...
Лю Юйин; И.А. Быкова. - : Zenodo, 2017
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4
Communicative-pragmatic disorders in traumatic brain injury: The role of theory of mind and executive functions
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