Abstract
We present the MultiScript Phonetic Search algorithm to address the problem of language learners looking up unfamiliar words that they heard. We apply it to Arabic dictionary lookup with noisy queries done using both the Arabic and Roman scripts. Our algorithm is based on a computational phonetic distance metric that can be optionally machine learned. To benchmark our performance, we created the ArabScribe dataset, containing 10,000 noisy transcriptions of random Arabic dictionary words. Our algorithm outperforms Google Translate’s “did you mean” feature, as well as the Yamli smart Arabic keyboard.- Anthology ID:
- W17-1315
- Volume:
- Proceedings of the Third Arabic Natural Language Processing Workshop
- Month:
- April
- Year:
- 2017
- Address:
- Valencia, Spain
- Venue:
- WANLP
- SIG:
- SEMITIC
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 119–129
- Language:
- URL:
- https://aclanthology.org/W17-1315
- DOI:
- 10.18653/v1/W17-1315
- Cite (ACL):
- Lingliang Zhang, Nizar Habash, and Godfried Toussaint. 2017. Robust Dictionary Lookup in Multiple Noisy Orthographies. In Proceedings of the Third Arabic Natural Language Processing Workshop, pages 119–129, Valencia, Spain. Association for Computational Linguistics.
- Cite (Informal):
- Robust Dictionary Lookup in Multiple Noisy Orthographies (Zhang et al., WANLP 2017)
- PDF:
- https://preview.aclanthology.org/starsem-semeval-split/W17-1315.pdf