{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/robsut-wrod-reocginiton-via-semi-character","title":"Robsut Wrod Reocginiton via semi-Character Recurrent Neural Network","arxiv_id":"1608.02214","date":"2016-08-07","proceeding":null,"authors":["Keisuke Sakaguchi","Kevin Duh","Matt Post","Benjamin Van Durme"],"abstract":"Language processing mechanism by humans is generally more robust than\ncomputers. The Cmabrigde Uinervtisy (Cambridge University) effect from the\npsycholinguistics literature has demonstrated such a robust word processing\nmechanism, where jumbled words (e.g. Cmabrigde / Cambridge) are recognized with\nlittle cost. On the other hand, computational models for word recognition (e.g.\nspelling checkers) perform poorly on data with such noise. Inspired by the\nfindings from the Cmabrigde Uinervtisy effect, we propose a word recognition\nmodel based on a semi-character level recurrent neural network (scRNN). In our\nexperiments, we demonstrate that scRNN has significantly more robust\nperformance in word spelling correction (i.e. word recognition) compared to\nexisting spelling checkers and character-based convolutional neural network.\nFurthermore, we demonstrate that the model is cognitively plausible by\nreplicating a psycholinguistics experiment about human reading difficulty using\nour model.","url_abs":"http://arxiv.org/abs/1608.02214v2","url_pdf":"http://arxiv.org/pdf/1608.02214v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"robsut-wrod-reocginiton-via-semi-character","repo_url":"https://github.com/simonroquette/CORAP","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"spelling-correction","task_name":"Spelling Correction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1608.02214","atlas_url":"https://app.syntology.ai/?focus=1608.02214","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1608.02214"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/simonroquette/CORAP","reach":null}],"summary":{"ran_draft_wrong":2},"by_repo_kind":{"listed":{"samples":1,"ran":1,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":2,"samples":[{"code_sha256_prefix":"5a827e391309a388","entry":"colors","repo":"simonroquette/CORAP","repo_kind":"listed","path":"predict.py","file_url":"https://github.com/simonroquette/CORAP/blob/HEAD/predict.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"5a827e391309a388"}},{"code_sha256_prefix":"b91a5961fb87cb5e","entry":"load_obj","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"b91a5961fb87cb5e"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}