Nonlinguistic Information Extraction by Semi-Supervised Techniques


Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International Conference on Informatics in Control, Automation and Robotics, ICINCO 2017; Madrid; Madrid

Год издания: 2017

Ключевые слова: Nonlinguistic Information Extraction, Semi-supervised learning, bio-inspired algorithms, evolutionary algorithms

Аннотация: The concept of nonlinguistic information includes all types of extra linguistic information such as factors of age, emotion and physical states, accent and others. Semi-supervised techniques based on using both labelled and unlabelled examples can be an efficient tool for solving nonlinguistic information extraction problems with lПоказать полностьюarge amounts of unlabelled data. In this paper a new cooperation of biology related algorithms (COBRA) for semi-supervised support vector machines (SVM) training and a new selfconfiguring genetic algorithm (SelfCGA) for the automated design of semi-supervised artificial neural networks (ANN) are presented. Firstly, the performance and behaviour of the proposed semi-supervised SVMs and semi-supervised ANNs were studied under common experimental settings; and their workability was established. Then their efficiency was estimated on a speech-based emotion recognition problem.

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Журнал: ICINCO 2017

Выпуск журнала: 1

Номера страниц: 312-317

Издатель: SCITEPRESS – Science and Technology Publications


  • Semenkina M. (Reshetnev Siberian State University of Science and Technology)
  • Akhmedova Sh. (Reshetnev Siberian State University of Science and Technology)
  • Semenkin E. (Reshetnev Siberian State University of Science and Technology)

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