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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) The Indonesian Journal of Computer Science
Pourmousa, Hadi
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Lip reading using deep learning in Turkish language Pourmousa, Hadi; Özen, Üstün
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp3250-3261

Abstract

Computer vision is one of the most important areas of artificial intelligence and lip reading is one of the most important areas of computer vision. Lip-reading, which is more important in noisy environments or where there is no sound flow, is one of the working areas that can help the hearing-impaired people. There is no dataset in Turkish for lip reading, which there are different datasets at alphabet, word, and sentence level in different languages. The dataset of this study was created by the author and video data were collected from 72 people for 71 words. Audio streams were removed from the collected videos and a dataset was created using only images. Due to the small size of the dataset, the data was replicated with the Camtasia application. After the model of the research was designed and trained, the model was tested on adjectives, nouns, and verbs dataset and success rates of 71.8%, 71.88%, and 79.69% were obtained, respectively.
Exploring AutoText Summarization Methods in Turkish: A Literature Review Alipour, Neda; Pourmousa, Hadi; Naserinia, Mohammad
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4803

Abstract

In recent years, the huge volume of textual data has become a challenge, as this challenge is seen in various fields, including scientific articles, legal documents, Internet archives, and even online product reviews. Given the limited data processing capacity of humans, processing large amounts of data is impractical and causes confusion; on the other hand, it requires a lot of effort, which ultimately results in a waste of time. To overcome this problem, the need to implement automated techniques such as automatic text summarization has emerged. Automated text summarization is an automated technique used to create a more condensed version of the original content that provides the same meaning and information. In fact, the generated output should contain important information from the original document. Various techniques for automatic summarization have been proposed in studies. Many studies have been presented on automatic text summarization methods, however, limited papers have contributed to reviewing different techniques of summarization methods in different languages, so this topic is evolving to reach maturity. This study focuses on different automatic text summarization methods in Turkish by reviewing the literature and previous studies, thus analyzing the performance of automatic text summarization methods.
Co-Authors Alipour, Neda Naserinia, Mohammad Özen, Üstün