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| "paper_id": "E99-1042", | |
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| "date_generated": "2023-01-19T10:37:24.528186Z" | |
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| "title": "Simplifying Text for Language-Impaired Readers", | |
| "authors": [ | |
| { | |
| "first": "John", | |
| "middle": [], | |
| "last": "Carroll", | |
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| "institution": "University of Sussex", | |
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| "settlement": "Brighton", | |
| "country": "UK" | |
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| { | |
| "first": "Guido", | |
| "middle": [], | |
| "last": "Minnen", | |
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| "institution": "University of Sussex", | |
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| "settlement": "Brighton", | |
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| } | |
| }, | |
| "email": "guidomi@cogs.susx.ac.uk" | |
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| "first": "Darren", | |
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| "last": "Pearce", | |
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| "email": "darrenpg@cogs.susx.ac.uk" | |
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| "first": "Yvonne", | |
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| "last": "Canning", | |
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| "first": "Siobhan", | |
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| "last": "Devlin", | |
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| "last": "Tait", | |
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| "text": "Automatic text simpli cation for languageimpaired readers is a relatively unexplored area in natural language processing. We describe a generic system for text simpli cation (currently at the prototype stage) incorporating a range of state-of-the-art language processing tools. We are applying the system to help people with aphasia (various language impairments, typically occurring as a result of a stroke or head injury) to understand English newspaper articles 1 .", | |
| "cite_spans": [], | |
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| "section": "Introduction", | |
| "sec_num": "1" | |
| }, | |
| { | |
| "text": "Aphasic people may encounter many problems when reading. It has been demonstrated (Devlin, 1999 ) that these problems can be of a lexical nature since less frequent words are often not readily available, and also of a syntactic nature in that particular constructions may pose serious di culties for understanding. In addition to these general aspects of text, there are also problems speci c to newspaper text; for example, the often very compact summary-like rst paragraph in an article; long sentences; the use of noun compounds and long sequences of adjectives; and frequent use of the passive. Although there is wide variation in the language problems associated with aphasia, depending on such factors as locus of brain injury, aphasia type, and pre-aphasic literacy level, many aphasic people would bene t from a system of the sort we describe.", | |
| "cite_spans": [ | |
| { | |
| "start": 82, | |
| "end": 95, | |
| "text": "(Devlin, 1999", | |
| "ref_id": "BIBREF6" | |
| } | |
| ], | |
| "ref_spans": [], | |
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| "section": "Introduction", | |
| "sec_num": "1" | |
| }, | |
| { | |
| "text": "We outline below the processing strategy of the system and the user-centered evaluation we intend to carry out. We envisage that the results of this project will be of use not only to aphasic individuals, but also to other groups such as non-native speakers whose comprehension of written English text is restricted by limited foreign language skills.", | |
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| "section": "Introduction", | |
| "sec_num": "1" | |
| }, | |
| { | |
| "text": "1 This work is being carried out on the project PSET: Practical Simpli cation of English Text' funded by the UK EPSRC (refs GR/L53175 and GR/L53175).", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
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| "section": "Introduction", | |
| "sec_num": "1" | |
| }, | |
| { | |
| "text": "The rst author is supported by an EPSRC Advanced Fellowship. Further information about PSET is available at <http://osiris.sunderland.ac.uk/~pset/welcome.html>.", | |
| "cite_spans": [], | |
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| "section": "Introduction", | |
| "sec_num": "1" | |
| }, | |
| { | |
| "text": "We download the original newspaper articles automatically from the WWW 2 , and apply a number of processing stages sequentially.", | |
| "cite_spans": [], | |
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| "eq_spans": [], | |
| "section": "The System", | |
| "sec_num": "2" | |
| }, | |
| { | |
| "text": "Lexical Tagger The tagger (Elworthy, 1994) assigns and ranks part-of-speech (PoS) tags for each word in a sentence using a rst-order HMM. The tagger includes an unknown word guesser with an accuracy of around 85%, and a large diskresident lexicon specialised to newspaper text.", | |
| "cite_spans": [ | |
| { | |
| "start": 26, | |
| "end": 42, | |
| "text": "(Elworthy, 1994)", | |
| "ref_id": "BIBREF7" | |
| } | |
| ], | |
| "ref_spans": [], | |
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| "section": "The System", | |
| "sec_num": "2" | |
| }, | |
| { | |
| "text": "analyser (an enhanced version of the GATE project lemmatiser (Cunningham et al., 1996) ) is based on nite state techniques, and performs an accurate and e cient in ectional analysis of the words in a text given the PoS assignment made by the tagger.", | |
| "cite_spans": [ | |
| { | |
| "start": 61, | |
| "end": 86, | |
| "text": "(Cunningham et al., 1996)", | |
| "ref_id": "BIBREF4" | |
| } | |
| ], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Morphological Analyser The morphological", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "Parser The parser uses a robust feature-based uni cation grammar of PoS and punctuation tags (Briscoe and Carroll, 1995) , coupled with probabilistic LR disambiguation (Carroll and Briscoe, 1996) , assigning the most plausible`shallow' phrase structure analysis to the PoS network (lattice) returned by the tagger. Coverage of a substantial corpus of general text is around 80%. We will improve coverage by utilising recent grammar learning techniques (Osborne, Submitted) to dynamically improve coverage in a principled and tractable manner.", | |
| "cite_spans": [ | |
| { | |
| "start": 93, | |
| "end": 120, | |
| "text": "(Briscoe and Carroll, 1995)", | |
| "ref_id": "BIBREF1" | |
| }, | |
| { | |
| "start": 168, | |
| "end": 195, | |
| "text": "(Carroll and Briscoe, 1996)", | |
| "ref_id": "BIBREF2" | |
| }, | |
| { | |
| "start": 452, | |
| "end": 472, | |
| "text": "(Osborne, Submitted)", | |
| "ref_id": null | |
| } | |
| ], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Morphological Analyser The morphological", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "Anaphor Resolver The anaphor resolution component (the only stage not as yet implemented in any form) will be based on CogNIAC (Baldwin, 1997) , but rewritten to take advantage of the preceding processing.", | |
| "cite_spans": [ | |
| { | |
| "start": 127, | |
| "end": 142, | |
| "text": "(Baldwin, 1997)", | |
| "ref_id": "BIBREF0" | |
| } | |
| ], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Morphological Analyser The morphological", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "problems with syntactic constructions that deviate from canonical subject-verb-object order.", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Syntactic Simpli er Aphasic people may have", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "Thus, passive sentences such as The scheme was singled out by a recent Government report are found di cult 3 , despite the presence of the syntactic cues was, -ed and by. We therefore replace passive constructions with corresponding active forms. We are currently integrating further rules to split conjoined sentences and extract embedded clauses. Syntactic simpli cation operates iteratively until a con guration is reached that cannot be simpli ed. This approach is broadly similar to that proposed by (Chandrasekar et al., 1996) .", | |
| "cite_spans": [ | |
| { | |
| "start": 505, | |
| "end": 532, | |
| "text": "(Chandrasekar et al., 1996)", | |
| "ref_id": "BIBREF3" | |
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| ], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Syntactic Simpli er Aphasic people may have", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "One of the many challenges in syntactic simplication is the observed e ect of the total length of a text being increased when longer sentences are replaced by multiple shorter ones. Also, the removal of cohesive devices such as conjunctions may result in anaphora crossing sentence boundaries. To maintain text coherence and cohesion (Grodzinsky et al., 1993) an anaphor is replaced by its referent if the containing sentence is split.", | |
| "cite_spans": [ | |
| { | |
| "start": 334, | |
| "end": 359, | |
| "text": "(Grodzinsky et al., 1993)", | |
| "ref_id": "BIBREF8" | |
| } | |
| ], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Syntactic Simpli er Aphasic people may have", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "Lexical Simpli er The lexical simpli er (based on (Devlin, 1999; Devlin and Tait, 1998) ) replaces content words with simpler synonyms. It rst retrieves a set of synonyms for each word from WordNet (Miller et al., 1993) , then, according to the user's desired level of simpli cation, the original word plus a percentage of the synonym list are looked up in the Oxford Psycholinguistic Database (Quinlan, 1992) for the corresponding Kucera-Francis frequencies. The word with the highest frequency is selected.", | |
| "cite_spans": [ | |
| { | |
| "start": 50, | |
| "end": 64, | |
| "text": "(Devlin, 1999;", | |
| "ref_id": "BIBREF6" | |
| }, | |
| { | |
| "start": 65, | |
| "end": 87, | |
| "text": "Devlin and Tait, 1998)", | |
| "ref_id": "BIBREF5" | |
| }, | |
| { | |
| "start": 198, | |
| "end": 219, | |
| "text": "(Miller et al., 1993)", | |
| "ref_id": "BIBREF9" | |
| }, | |
| { | |
| "start": 394, | |
| "end": 409, | |
| "text": "(Quinlan, 1992)", | |
| "ref_id": "BIBREF12" | |
| } | |
| ], | |
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| "section": "Syntactic Simpli er Aphasic people may have", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "works on the in ectionally analysed text, so the last stage is morphological generation. The generator is simply an inverted version of the morphological analyser described above. The inversion is performed automatically (Minnen and Carroll, Submitted) , so any improvements made to the analyser are re ected in the generator at no extra cost. Finally, inter-word spelling changes (e.g. a apple ! an apple), auxiliary reduction, etc. are performed.", | |
| "cite_spans": [ | |
| { | |
| "start": 221, | |
| "end": 252, | |
| "text": "(Minnen and Carroll, Submitted)", | |
| "ref_id": null | |
| } | |
| ], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Morphological Generator Simpli cation", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "We will perform an experimental evaluation of the system with the help of aphasic participants who are matched to the extent that none display visually related reading di culties, which would confound the results, and all possess a su ciently high reading ability|determined at the time of the experiment by using an aphasia assessment battery. As the system is a general tool aimed at all aphasics, the participants will not be screened for aphasia type. The readability of the simplied text and the usability of the system will be assessed by observation and interview; questions will be posed to gauge subjects' comprehension of both explicit and implicit material.", | |
| "cite_spans": [], | |
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| "section": "Evaluation", | |
| "sec_num": "3" | |
| }, | |
| { | |
| "text": "We are using a local newspaper in the north-east of England, The Sunderland Echo, that is also published online.", | |
| "cite_spans": [], | |
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| "section": "", | |
| "sec_num": null | |
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| { | |
| "text": "Semantically reversible sentences such as The boy was kissed by the girl are even more di cult, since either noun phrase could be the subject.", | |
| "cite_spans": [], | |
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| "BIBREF0": { | |
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