Quantitative classification of conversational language using artificial neural networks

References

• Albert , M. L. , Goodglass , H. , Helm , N. A. , Rubens , A. B. and Alexander , M. P. 1981 . Clinical Aspects of Dysphasia , New York : Springer .
   Google Scholar
• Andrews , D. F. 1972 . Plots of high‐dimensional data . Biometrics , 28 : 125 – 136 .
   Web of Science ®Google Scholar
• Berndt , R. and Caramazza , A. 1980 . A redefinition of the syndrome of Broca's aphasia: implications for a neuropsychological model of language . Applied Psycholinguistics , 1 : 225 – 278 .
   Web of Science ®Google Scholar
• Brunet , E. 1978 . “ Le Vocabulaire de Jean Giraudoux ” . In Structure et Evolution , Edited by: Brunet , E. Geneva : Slatkine .
   Google Scholar
• Byng , S. , Kay , J. , Edmundson , A. and Scotts , C. 1990 . Clinical forum–aphasia tests reconsidered . Aphasiology , 4 : 67 – 91 .
   Web of Science ®Google Scholar
• Code , C. , Rowley , D. and Kertesz , A. 1994 . Predicting recovery from aphasia with connectionist networks: preliminary comparisons with multiple regression . Cortex , 30 : 527 – 532 .
   PubMed Web of Science ®Google Scholar
• Crockford , C. and Lesser , R. 1994 . Assessing functional communication in aphasia: clinical utility and time demands of three methods . European Journal of Disorders of Communication , 29 : 165 – 182 .
   PubMedGoogle Scholar
• Everitt , B. and Dunn , G. 1991 . Applied Multivariate Data Analysis , London : Edward Arnold .
   Google Scholar
• Fletcher , P. and Garman , M. 1988 . LARSPing by numbers . British Journal of Disorders of Communication , 23 : 309 – 321 .
   Google Scholar
• Fu , L. 1994 . Neural networks in Computer Intelligence , 331 – 348 . Singapore : McGraw‐Hill .
   Google Scholar
• Goodglass , H. , Quadfasel , F. A. and Timberlake , W. H. 1964 . Phrase length and type and severity of aphasia . Cortex , 1 : 133 – 153 .
   Google Scholar
• Hockey , S. and Martin , J. 1988 . OCP—Users' Manual , Oxford University Computing Service .
   Google Scholar
• Holmes , D. I. 1992 . A stylometric analysis of Mormon scripture and related texts . Journal of the Royal Statistical Society (A) , 155 : 91 – 120 .
   Google Scholar
• Holmes , D. I. 1994 . Authorship attribution . Computers and the Humanities , 28 : 87 – 106 .
   Google Scholar
• Holmes , D. I. and Singh , S. 1996 . A stylometric analysis of conversational speech of aphasic patients . Literary and Linguistic Computing , 11 : 133 – 140 .
   Google Scholar
• Honore , A. 1979 . Some simple measures of richness of vocabulary . Association of Literary and Linguistic Computing Bulletin , 7 : 172 – 177 .
   Google Scholar
• Howes , D. H. 1964 . “ Application of the word‐frequency concept of aphasia ” . In Disorders of Language , Edited by: de Rueck , A. V. S. and O'Connor , M. 49 – 67 . London : Ciba Foundation Symposium/Churchill .
   Google Scholar
• Jollife , I. T. 1986 . Principal Components Analysis , New York : Springer‐Verlag .
   Google Scholar
• Kerchensteiner , M. , Poeck , K. and Brunner , E. 1972 . The fluency–non‐fluency dimension in aphasia . Cortex , 8 : 233 – 247 .
   PubMedGoogle Scholar
• Kertesz , A. 1979 . Western Aphasia Battery , New York : Grune & Stratton .
   Google Scholar
• Lesser , R. 1989 . Linguistic Investigations of Aphasia , 2nd edn , London : Whurr .
   Google Scholar
• Lesser , R. and Milroy , L. 1993 . Linguistics and Aphasia , London : Longman .
   Google Scholar
• Lesser , R. and Algar , L. 1995 . Towards combining the cognitive neuropsychological and the pragmatic in aphasia therapy . Neuropsychological Rehabilitation , 5 : 67 – 92 .
   Web of Science ®Google Scholar
• McMurty , G. J. 1994 . “ Adaptive optimization procedures ” . In A Prelude to Neural Networks: Adaptive and learning systems , Edited by: Mendel , J. M. 252 – 256 . CA : Prentice‐Hall .
   Google Scholar
• Miller , J. and Chapman , R. 1993 . Systematic Analysis of Language Transcripts (SALT) , Madison, WI : Language Analysis Laboratory, Waisman Center, University of Wisconsin . [Computer Software, MS‐DOS version 3.0]
   Google Scholar
• Saffran , E. M. , Berndt , R. and Schwartz , M. F. 1989 . The quantitative analysis of agrammatic production: procedure and data . Brain and Language , 37 : 440 – 479 .
   PubMed Web of Science ®Google Scholar
• Singh , S. Linguistic computing in speech and language disorders . Proceedings of the 5th International Conference on Speech Science and Technology . vol. 2 , pp. 486 – 491 . Perth
   Google Scholar
• Singh , S. Computational linguistics for analyzing conversation in speech and language disorders . Proceedings of the 3rd International Conference on the Statistical Analysis of Textual Data . vol. 1 , pp. 355 – 362 . Rome
   Google Scholar
• Singh , S. 1996 . Computational analysis of conversational speech of dysphasic patients , PhD dissertation UK : University of the West of England .
   Google Scholar
• Stone , M. 1974 . Cross‐validatory choice and assessment of statistical predictions . Journal of the Royal Statistical Society , 36 : 111 – 147 .
   Google Scholar
• Tweedie , F. and Singh , S. Neural network applications in stylometry: the federalist papers . Proceedings of the 3rd International Conference on the Cognitive Science of Natural Language Processing . pp. 1 – 8 . Dublin : Dublin City University .
   Google Scholar
• Wagenaar , E. , Snow , C. and Prins , R. 1975 . Spontaneous speech of aphasic patients: a psycholinguistic analysis . Brain and Language , 2 : 281 – 303 .
   PubMed Web of Science ®Google Scholar
• Wepman , J. M. and Jones , L. V. 1966 . Studies in aphasia: classification of aphasic speech by the noun–pronoun ratio . British Journal of Disabilities of Communication , 1 : 46 – 54 .
   Google Scholar
• Whurr , R. 1988 . “ Assessment of treatment in aphasia ” . In Aphasia , Edited by: Rose , F. C. , Whurr , R. and Wyke , M. A. 518 – 548 . London : Whurr .
   Google Scholar
• Zipf , G. K. 1932 . Selected Studies of the Principle of Relative Frequency in Language , Cambridge, MA : Harvard University Press .
   Google Scholar