Skip to main content
Log in

Deliberate word access: an intuition, a roadmap and some preliminary empirical results

  • Published:
International Journal of Speech Technology Aims and scope Submit manuscript

Abstract

No doubt, words play a major role in language production, hence finding them is of vital importance, be it for writing or for speaking (spontaneous discourse production, simultaneous translation). Words are stored in a dictionary, and the general belief holds, the more entries the better. Yet, to be truly useful the resource should contain not only many entries and a lot of information concerning each one of them, but also adequate navigational means to reveal the stored information. Information access depends crucially on the organization of the data (words) and the access keys (meaning/form), two factors largely overlooked. We will present here some ideas of how an existing electronic dictionary could be enhanced to support a speaker/writer to find the word s/he is looking for. To this end we suggest to add to an existing electronic dictionary an index based on the notion of association, i.e. words co-occurring in a well balanced corpus, the latter being supposed to represent the average citizen’s knowledge of the world. Before describing our approach, we will briefly take a critical look at the work being done by colleagues working on automatic, spontaneous or deliberate language production,—that is, computer-generated language, simulation of the mental lexicon, or WordNet (WN),—to see how adequate they are with regard to our goal.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Agirre, E., Ansa, O., Martinez, D., & Hovy, E. (2001). Enriching WordNet concepts with topic signatures. In NAACL’01 workshop on WordNet and other lexical resources: applications, extensions and customizations.

  • Aitchinson, J. (2003). Words in the mind: an introduction to the mental lexicon. Oxford: Blackwell.

    Google Scholar 

  • Avancini, H., Lavelli, A., Magnini, B., Sebastiani, F., & Zanoli, R. (2003). Expanding domain-specific lexicons by term categorization. In 18th ACM symposium on applied computing (SAC-03).

  • Baddeley, A. (1982). Your memory: a user’s guide. Baltimore: Penguin.

    Google Scholar 

  • Barabási, A. (2002). Linked: the new science of networks. Cambridge: Perseus.

    Google Scholar 

  • Buchanan, M. (2002). Nexus: small worlds and the groundbreaking theory of networks. New York: W.W. Norton.

    Google Scholar 

  • Bateman, J., & Zock, M. (2003). Natural language generation. In R. Mitkov (Ed.), Handbook of computational linguistics (pp. 284–304). Oxford: Oxford University Press.

    Google Scholar 

  • Beeferman, D., Berger, A., & Lafferty, J. (1999). Statistical models for text segmentation. Machine Learning, 34(1), 177–210.

    Article  MATH  Google Scholar 

  • Boissière, P. (1862). Dictionnaire analogique de la langue française : répertoire complet des mots par les idées et des idées par les mots, Paris.

  • Bonin, P. (2004). Mental lexicon: some words to talk about words. New York: Nova Science Publishers.

    Google Scholar 

  • Brown, R., & McNeill, D. (1996). The tip of the tongue phenomenon. Journal of Verbal Learning and Verbal Behaviour, 5, 325–337.

    Article  Google Scholar 

  • Burke, D. M., MacKay, D. G., Worthley, J. S., & Wade, E. (1991). On the tip of the tongue: what causes word finding failures in young and older adults? Journal of Memory and Language, 30, 542–579.

    Article  Google Scholar 

  • Cahill, L., & Reape, M. (1999). Lexicalisation in applied NLG systems (p. 9). Brighton: ITRI.

    Google Scholar 

  • Church, K., & Hanks, P. (1990). Word association norms, mutual information, and lexicography. Computational Linguistics, 16(1), 177–210.

    Google Scholar 

  • Collins, A., & Quillian, L. (1969). Retrieval time from semantic memory. Journal of Verbal Learning and Verbal Behavior, 8, 240–247.

    Article  Google Scholar 

  • Cumming, S. (1986). The lexicon in text generation. ISI: 86–168.

  • Cutler, A. (Ed.) (1982). Slips of the tongue and language production. Amsterdam: Mouton.

    Google Scholar 

  • Deese, J. (1965). The structure of associations in language and thought. Baltimore: Johns Hopkins Press.

    Google Scholar 

  • Dell, G. S. (1986). A spreading-activation theory of retrieval in sentence production. Psychological Review, 93, 283–321.

    Article  Google Scholar 

  • Dong, Z., & Dong, Q. (2006). HOWNET and the computation of meaning. London: World Scientific.

    Book  Google Scholar 

  • Dutoit, D., & Nugues, P. (2002). A lexical network and an algorithm to find words from definitions. In F. van Harmelen (Ed.), ECAI2002, Proceedings of the 15th European conference on artificial intelligence, Lyon (pp. 450–454).

    Google Scholar 

  • El-Kahlout, I. D., & Oflazer, K. (2004). Use of wordnet for retrieving words from their meanings. In 2nd Global WordNet conference, Brno.

  • Fellbaum, C. (1998). WordNet: an electronic lexical database and some of its applications. Cambridge: MIT Press.

    Google Scholar 

  • Ferret, O. (2002). Using collocations for topic segmentation and link detection. In COLING 2002 (pp. 260–266).

    Google Scholar 

  • Ferret, O. (2006). Building a network of topical relations from a corpus. In LREC 2006.

  • Ferret, O., & Zock, M. (2006) Enhancing electronic dictionaries with an index based on associations. In ACL’06: Proceedings of the 21st international conference on computational linguistics and the 44th annual meeting of the ACL (pp. 281–288).

  • Fontenelle, T. (1997). Using a bilingual dictionary to create semantic networks. International Journal of Lexicography, 10(4):275–303.

    Article  Google Scholar 

  • Fromkin, V. (Ed.) (1973). Speech errors as linguistic evidence. The Hague: Mouton Publishers.

    Google Scholar 

  • Goddard, C. (1998). Bad arguments against semantic primitives. Theoretical Linguistics, 24(23), 129–156.

    Article  Google Scholar 

  • Goldman, N. (1975). Conceptual generation. In R. Schank (Ed.), Conceptual information processing. Amsterdam: North-Holland.

    Google Scholar 

  • Hanks, P., & Pustejovsky, J. (2005). A pattern dictionary for natural language processing’ in revue française de linguistique appliquée 10 (2).

  • Harabagiu, S., & Moldovan, D. (1998). Knowledge processing on extended WordNet. In C. Fellbaum (Ed.), WordNet: an electronic lexical database and some of its applications (pp. 379–405) Cambridge: MIT Press.

    Google Scholar 

  • Harley, T. (2010). Talking the talk. New York: Psychology Press.

    Google Scholar 

  • Jarema, G., Libben, G., & Kehayia, E. (2002). The mental lexicon. Brain and Language, 81.

  • Jung, C., & Riklin, F. (1906). Experimentelle Untersuchungen Über Assoziationen Gesunder. In Jung, C. G. (Ed.), Diagnostische Assoziationsstudien (pp. 7–145) Leipzig: Barth.

    Google Scholar 

  • Kempen, G., & Huijbers, P. (1983). The lexicalization process in sentence production and naming: Indirect election of words. Cognition, 14, 185–209.

    Article  Google Scholar 

  • Kilgarriff, A., Rychly, P., Smrz, P., & Tugwell, D. (2004). The sketch engine. In Proceedings of the eleventh EURALEX international congress, Lorient, France (pp. 105–116).

    Google Scholar 

  • Lamb, S. (1999). Pathways of the brain: the neurocognitive basis of language. Amsterdam: John Benjamins.

    Google Scholar 

  • Levelt, W. (1992). Accessing words in speech production: stages, processes and representations. Cognition, 42, 1–22.

    Article  Google Scholar 

  • Levelt, W. J. M., Roelofs, A., & Meyer, A. S. (1999). A theory of lexical access in speech production. Behavioral and Brain Sciences, 22, 1–75.

    Google Scholar 

  • Magnini, B., & Cavaglia, G. (2000). Integrating subject field codes into WordNet. In Second international conference on language resources and evaluation, Athenes, Geece (pp. 1413–1418).

    Google Scholar 

  • Mandala, R., Tokunaga, T., & Tanaka, H. (1999). Complementing WordNet with Roget’s and corpus-based thesauri for information retrieval. In EACL99.

  • Marslen-Wilson, W. (Ed.) (1979). Lexical representation and process, Bradford book. Cambridge: MIT Press.

    Google Scholar 

  • Mel’čuk, I., Arbatchewsky-Jumarie, N., Iordanskaja, L., Mantha, S., & Polguère, A. (1999). In Recherches lexico-séman-tiques IV. Dictionnaire explicatif et combinatoire du français contemporain. Montréal: Les Presses de l’Université de Montréal.

    Google Scholar 

  • Mihalcea, R., & Moldovan, D. (2001). Extended WordNet: progress report. In NAACL 2001—workshop on WordNet and other lexical resources, Pittsburgh, USA.

  • Miller, G. A. (Ed.) (1990). WordNet: an on-line lexical database. International Journal of Lexicography, 3(4), 235–244.

    Article  Google Scholar 

  • Moerdijk, F. (2008). Frames and semagrams; meaning description in the general dutch dictionary. In Proceedings of the thirteenth Euralex international congress, EURALEX, Barcelona.

  • Nicolov, N. (1999). Approximate text generation from non-hierarchical representation in a declarative framework. PhD dissertation, university of Edinburgh.

  • Nogier, J. F., & Zock, M. (1992). Lexical choice by pattern matching. Knowledge Based Systems, 5(3), 200–212.

    Article  Google Scholar 

  • Richardson, S. W., Dolan, B., & Vanderwende, L. (1998). MindNet: acquiring and structuring semantic information from text. In ACL-COLING’98 (pp. 1098–1102).

    Google Scholar 

  • Robin, J. (1990). A survey of lexical choice in natural language generation. Technical Report CUCS 040-90, Dept. of Computer Science, University of Columbia.

  • Roelofs, A. (1992). A spreading-activation theory of lemma retrieval in speaking. In Cognition, 42, 107–142. W. Levelt (Ed.) Special issue on the lexicon.

    Article  Google Scholar 

  • Roget, P. (1852). Thesaurus of English words and phrases. London: Longman.

    Google Scholar 

  • Rundell, M. (2002). Macmillan English dictionary for advanced learners. Oxford: Macmillan.

    Google Scholar 

  • Sharoff, S. (2005). The communicative potential of verbs of ‘away-from’ motion in English and Russian. Functions of Language, 12(2), 203–238.

    Article  Google Scholar 

  • Schvaneveldt, R. (Ed.) (1989). Pathfinder Associative Networks: studies in knowledge organization. Norwood: Ablex.

    Google Scholar 

  • Sierra, G. (2000). The onomasiological dictionary: a gap in lexicography. In Proceedings of the ninth Euralex international congress, IMS, Universität Stuttgart (pp. 223–235).

    Google Scholar 

  • Sinopalnikova, A., & Smrz, P. (2006). Knowing a word vs. accessing a word: Wordnet and word association norms as interfaces to electronic dictionaries. In Proceedings of the third international WordNet conference, Korea (pp. 265–272).

    Google Scholar 

  • Smith, E., Shoben, E., & Rips, L. (1974). Structure and process in semantic memory: a featural model for semantic decisions. Psychological Review, 81, 214–241.

    Article  Google Scholar 

  • Stede, M. (1995). Lexicalization in natural language generation: a survey. Artificial Intelligence Review, 8, 309–336.

    Article  Google Scholar 

  • Stemberger, N. (1985). The lexicon in a model of speech production. New York: Garland.

    Google Scholar 

  • Summers, D. (1993). Language Activator: the world’s first production dictionary. London: Longman.

    Google Scholar 

  • T’ong, T.-K. (1862). Ying ü tsap ts’ün (The Chinese and English instructor). Canton.

  • Vigliocco, G., Antonini, T., & Garrett, M. F. (1997). Grammatical gender is on the tip of Italian tongues. Psychological Science, 8, 314–317.

    Article  Google Scholar 

  • Wanner, L. (1996). Lexical choice in text generation and machine translation. Machine Translation, 11, 3–35. Choice. L. W. (Ed.) Special Issue on Lexical.

    Article  Google Scholar 

  • Ward, N. (1988). Issues in word choice. COLING-88, Budapest.

  • Zock, M., & Bilac, S. (2004). Word lookup on the basis of associations: from an idea to a roadmap. In Proc. of coling workshop: Enhancing and using dictionaries, Geneva (pp. 29–35).

    Chapter  Google Scholar 

  • Zock, M., & Schwab, D. (2010). Lexical access, a search problem. In Cogalex-2, Beijing.

  • Zock, M., & Schwab, D. (2008). Lexical access based on underspecified input. In Cogalex-1, coling workshop, Manchester.

  • Zock, M. (1996). The power of words in message planning, COLING, Copenhagen, 990-5. http://acl.ldc.upenn.edu/C/C96/C96-2167.pdf.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Michael Zock.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zock, M., Ferret, O. & Schwab, D. Deliberate word access: an intuition, a roadmap and some preliminary empirical results. Int J Speech Technol 13, 201–218 (2010). https://doi.org/10.1007/s10772-010-9078-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10772-010-9078-9

Keywords

Navigation