文献の詳細
論文の言語 | 英語 |
---|---|
著者 | Rina Buoy, Masakazu Iwamura, Sovila Srun, Koichi Kise |
論文名 | Language-Aware Non-Autoregressive Khmer Textline Recognition Using Khmer Subword Model |
論文誌名 | Proc. International Conference on Pattern Recognition and Artificial Intelligence |
ページ数 | 16 pages |
査読の有無 | 有 |
発表の種類 | 口頭発表 |
年月 | 2024年7月 |
要約 | Unlike the Latin script, Khmer does not use spaces between words, leading to text recognition typically being done at the textline level. This can involve a vast number of characters and results in high latency for a language-aware autoregressive (AR) decoder that generates one character at a time. On the other hand, a non-autoregressive (NAR) decoder generates all characters in parallel, but it is not language-aware. In this paper, we introduce an efficient Khmer textline recognition method based on a NAR decoder, ensuring low decoding latency while maintaining linguistic awareness. This is achieved by utilizing a Khmer-specific subword modeling called Khmer character clusters (KCC) that capture the syntactic, morphological, and orthographic aspects of the Khmer script. Therefore, instead of conventional character-level recognition, the proposed method recognizes all character clusters or subwords in parallel. The experimental results demonstrate that the proposed method outperforms the character-level baseline NAR model in terms of recognition accuracy while maintaining the same low latency. When compared with the character-level baseline AR model, the proposed method achieves comparable or improved recognition accuracy while also achieving significantly lower latency. When compared with the recent state-of-the-art (SOTA) NAR and AR Khmer text recognition methods, our proposed method achieves superior recognition performance. |
- BibTeX用エントリー
@InProceedings{Buoy2024, author = {Rina Buoy and Masakazu Iwamura and Sovila Srun and Koichi Kise}, title = {Language-Aware Non-Autoregressive Khmer Textline Recognition Using Khmer Subword Model}, booktitle = {Proc. International Conference on Pattern Recognition and Artificial Intelligence}, year = 2024, month = jul, numpages = {16} }