
Image Caption Generator for Sinhala Using Deep Learning
Abstract
In this study, for the image caption generation in the Sinhala language, we have implemented a Recurrent Neural Network based model consisting of an InceptionV3 model as an image feature extraction model and a Long Short Term Memory network for the language model by referring to the literature. The different variations of Sinhala versions of the Flickr8K and MS COCO datasets have been constructed and used to train experimental models. Evaluation of the generated captions has been done using both automated and manual approaches. The model trained on the MS COCO dataset with Google translated Sinhala captions has achieved the highest BLEU score of 0.592 and the highest METEOR score of 0.281. After doing the manual caption analysis, it was observed that there could be generated captions which could provide a good idea to the reader while having lower BLEU and METEOR scores.
DOI: https://doi.org/10.4038/icter.v16i2.7266 | Journal eISSN: 2550-2794
Language: English
Page range: 40 - 46
Published on: Dec 8, 2023
Published by: University of Colombo School of Computing
In partnership with: Paradigm Publishing Services
Keywords:
© 2023 Damsara Ranasinghe, Randil Pushpananda, Ruvan Weerasinghe, published by University of Colombo School of Computing
This work is licensed under the Creative Commons Attribution 4.0 License.