Recently, it was proposed by Cai a new semantic/ syntactic/ episodic model of language encompassing the sentential meanings, while deriving three corresponding principles from it for machine translation, respectively as first to establish the dictionary of words/phrases, second to translate the grammar, and third to determine the meanings of some words/phrases of multiple meanings by statistical translation. In this article, it is discovered three types of episodic associations for this linguistic model, prospective in applications to statistical translation, as: 1) It is classified the living/natural words and phrases of multiple meanings by behavior, adopting both the zoological/ organizational/ physical/ categorical and affective/ behavioral/ logic/ characteristic/ changing characters to classify the nouns and verbs, the affective/ behavioral/ logic/ characteristic/ changing/ spatial/ temporal characters to the adjectives and adverbs, helpful to discern the meanings of them using these episodic associations with others within the sentence. 2) Likewise, it is classified the sentence/paragraph into the category of natural/social subjects like physics, biology, art, economy, etc., which was improved by the Chinese people in television from my original sentential/thematic category. 3) It is suggested to collect the frequent word-pairs during statistical translation, such as “bank money”, “war declaration”, etc., helpful to determine the episodic associations of some prepositions or terminal “which” clauses. It is suggested to use word episodic symbolization to apply them to computer. It is therefore improved the third principle of machine translation as third to determine the meanings of some words/ phrases of multiple meanings by episodic associations with others using the behavioral classification of words, the categorization of sentence/paragraph and the collection of frequent word-pairs.
Cite this paper
Cai, Z. (2017). Three Types of Episodic Associations for the Semantic/Syntactic/Episodic Model of Language Prospective in Applications to the Statistical Translation. Open Access Library Journal, 4, e3830. doi: http://dx.doi.org/10.4236/oalib.1103830.
Cai, Z.J. (2016) Principles Derived from Neurolinguistics of Brain for Design of Translation Machines. Open Access Library Journal, 3, e2704.
http://dx.doi.org/10.4236/oalib.1102704
Ullman, M.T., Corkin, S., Coppola, M., Hickok, G., Growdon, J.H., Koroshetz, W.J. and Pinker, S. (1997) A Neural Dissociation within Language: Evidence that the Mental Dictionary Is Part of Declarative Memory, and that Grammatical Rules Are Processed by the Procedural System. Journal of Cognitive Neuroscience, 9, 266-276.
https://doi.org/10.1162/jocn.1997.9.2.266
Stager, S.V., Calis, K., Grothe, D., Bloch, M., Berensen, N.M., Smith, P.J. and Braun, A. (2005) Treatment with Medications Affecting Dopaminergic and Serotonergic Mechanisms: Effects on Fluency and Anxiety in Persons Who Stutter. Journal of Fluency Disorders, 30, 319-335.
https://doi.org/10.1016/j.jfludis.2005.09.004
Lan, J., Song, M., Pan, C., Zhuang, G., Wang, Y., Ma, W., Chu, Q., Lai, Q., Xu, F., Li, Y., Liu, L. and Wang, W. (2009) Association between Dopaminergic Genes (SLC6A 3 and DRD2) and Stuttering among Han Chinese. Journal of Human Genetics, 54, 457-460.
https://doi.org/10.1038/jhg.2009.60
Small, S.L. and Llano, D.A. (2009) Biological Approaches to Aphasia Treatment. Current Neurology and Neuroscience Reports, 9, 443-450.
https://doi.org/10.1007/s11910-009-0066-x
Berthier, M.L., Pulvermüller, F., Dávila, G., Casares, N.G. and Gutiérrez, A. (2011) Drug Therapy of Post-Stroke Aphasia: A Review of Current Evidence. Neuropsychology Review, 21, 302-317.
https://doi.org/10.1007/s11065-011-9177-7
Cape, E.G., Manns, I.D., Alonso, A., Beaudet, A. and Jones, B.E. (2000) Neurotensin-Induced Bursting of Cholinergic Basal Forebrain Neurons Promotes Gamma and Theta Cortical Activity Together with Waking and Paradoxical Sleep. The Journal of Neuroscience, 20, 8452-8461.
Wang, L., Zhu, Z. and Bastiaansen, M. (2012) Integration or Predictability? A Further Specification of the Functional Role of Gamma Oscillations in Language Comprehension. Frontiers in Psychology, 3, 187.
https://doi.org/10.3389/fpsyg.2012.00187
Vidal, J.R., Freyermuth, S., Jerbi, K., Hamamé, C.M., Ossandon, T., Bertrand, O., Minotti, L., Kahane, P., Berthoz, A. and Lachaux, J.P. (2012) Long-Distance Amplitude Correlations in the High γ Band Reveal Segregation and Integration within the Reading Network. The Journal of Neuroscience, 32, 6421-6434.
https://doi.org/10.1523/JNEUROSCI.4363-11.2012
Weiss, S. and Müller, H.M. (2013) The Non-Stop Road from Concrete to Abstract: High Concreteness Causes the Activation of Long-Range Networks. Frontier in Human Neuroscience, 7, 526.
https://doi.org/10.3389/fnhum.2013.00526
Miniscalco, C., Hagberg, B., Kadesjo, B., Westerlund, M. and Gillberg, C. (2007) Narrative Skills, Cognitive Profiles and Neuropsychiatric Disorders in 7-8-Year-Old Children with Late Developing Language. International Journal of Language and Communication Disorders, 42, 665-681.
https://doi.org/10.1080/13682820601084428
Youse, K.M. and Coelho, C.A. (2009) Treating Underlying Attention Deficits as a Means for Improving Conversational Discourse in Individuals with Closed Head Injury: A Preliminary Study. Neurorehabilitation, 24, 355-364.
DiLollo, A., Neimeyer, R.A. and Manning, W.H. (2002) A Personal Construct Psychology View of Relapse: Indications for a Narrative Therapy Component to Stuttering Treatment. Journal of Fluency Disorders, 27, 19-40.
https://doi.org/10.1016/S0094-730X(01)00109-7
Leahy, M.M., O’Dwyer, M. and Ryan, F. (2012) Witnessing Stories: Definitional Ceremonies in Narrative Therapy with Adults Who Stutter. Journal of Fluency Disorders, 37, 234-241.
https://doi.org/10.1016/j.jfludis.2012.03.001
Zhang, M., Duan, X.Y. and Chen, W.L. (2014) Bayesian Constituent Context Model for Grammar Induction. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 22, 531-541.
https://doi.org/10.1109/TASLP.2013.2294584
Xiong, D.Y., Zhang, M. and Li, H.Z. (2011) A Maximum-Entropy Segmentation Model for Statistical Machine Translation. IEEE Transactions on Audio, Speech, and Language Processing, 19, 2494-2505.
https://doi.org/10.1109/TASL.2011.2144971
Xiong, D.Y., Zhang, M. and Wang, X. (2015) Topic-Based Coherence Modeling for Statistical Machine Translation. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 23, 483-493.
https://doi.org/10.1109/TASLP.2015.2395254