Semantic Hyper-graph Based Representation of Nouns in the Kazakh Language

Yergesh, Banu; Mukanova, Assel; Sharipbay, Altynbek; Bekmanova, Gulmira; Razakhova, Bibigul

doi:10.13053/cys-18-3-2041

Cited by 7 publications

(3 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The authors of the article carried out scientific work in the field of computerization of the Kazakh language, including published works on the morphological analysis of the text in the Kazakh language [13,14,15,16,17], as well as on syntactic and sentimental analysis [18,19,20,21,22].…”

Section: Ontological Model Of the Subject Ares In The Geagraphy Of Ka...mentioning

confidence: 99%

Development of an Ontological Knowledge Base for a Question–Answering System in the Kazakh Language

2023

International Conference Proceedings IICSET-23, ACBES-23 &Amp; LMSSH-23 Dec. 14-15, 2023 Istanbul (Turkiye)

View full text Add to dashboard Cite

This article describes a knowledge base based on an ontological model for a question-answering system in the Kazakh language. With the explosive growth of information and the constant accumulation of redundant information, it has become much more difficult to accurately and quickly obtain valuable information. The variety and volume of data available on the web require effective tools to extract, process and provide information to users. Therefore, the creation of an intelligent question-answering system in the Kazakh language based on the presentation, processing and extraction of knowledge can provide a significant contribution to improving access to information for Kazakh-speaking users. It also contributes to the preservation and promotion of the Kazakh language, expanding its presence in the digital space.

show abstract

Section: Ontological Model Of the Subject Ares In The Geagraphy Of Ka...mentioning

confidence: 99%

Development of an Ontological Knowledge Base for a Question–Answering System in the Kazakh Language

2023

International Conference Proceedings IICSET-23, ACBES-23 &Amp; LMSSH-23 Dec. 14-15, 2023 Istanbul (Turkiye)

View full text Add to dashboard Cite

show abstract

“…The works in [41] describe methods for determining the polarity of the text. When analyzing sentiment and emotion, the results of morphological [55,56] and syntactic analysis of the Kazakh language [57][58][59] are used.…”

Section: Current Alphabetmentioning

confidence: 99%

Emotional Speech Recognition Method Based on Word Transcription

Bekmanova

Yergesh

Sharipbay

et al. 2022

Sensors

Self Cite

View full text Add to dashboard Cite

The emotional speech recognition method presented in this article was applied to recognize the emotions of students during online exams in distance learning due to COVID-19. The purpose of this method is to recognize emotions in spoken speech through the knowledge base of emotionally charged words, which are stored as a code book. The method analyzes human speech for the presence of emotions. To assess the quality of the method, an experiment was conducted for 420 audio recordings. The accuracy of the proposed method is 79.7% for the Kazakh language. The method can be used for different languages and consists of the following tasks: capturing a signal, detecting speech in it, recognizing speech words in a simplified transcription, determining word boundaries, comparing a simplified transcription with a code book, and constructing a hypothesis about the degree of speech emotionality. In case of the presence of emotions, there occurs complete recognition of words and definitions of emotions in speech. The advantage of this method is the possibility of its widespread use since it is not demanding on computational resources. The described method can be applied when there is a need to recognize positive and negative emotions in a crowd, in public transport, schools, universities, etc. The experiment carried out has shown the effectiveness of this method. The results obtained will make it possible in the future to develop devices that begin to record and recognize a speech signal, for example, in the case of detecting negative emotions in sounding speech and, if necessary, transmitting a message about potential threats or riots.

show abstract

“…An applied ontology is based on general principles of ontology building, and semantic hyper-graphs are used as a model for knowledge representation. This formalism determines ontology O as triple (V, R, K), where V is a set of concepts of a given subject field, R is a set of relationships between these concepts, and K is a set of names of concepts and relationships in the domain [5,6,7,8].…”

Section: The Ontological Models Of Educational Programs In Computmentioning

confidence: 99%

Ontological Model of Educational Programs in Computer Science(Bachelor and Master Degrees)

2015

IJCCIE

View full text Add to dashboard Cite

show abstract

Semantic Hyper-graph Based Representation of Nouns in the Kazakh Language

Cited by 7 publications

References 18 publications

Development of an Ontological Knowledge Base for a Question–Answering System in the Kazakh Language

Development of an Ontological Knowledge Base for a Question–Answering System in the Kazakh Language

Emotional Speech Recognition Method Based on Word Transcription

Ontological Model of Educational Programs in Computer Science(Bachelor and Master Degrees)

Contact Info

Product

Resources

About