Correlation between Emotional States and Syntactic Speech Characteristics

1. Correlation between Emotional States and Syntactic Speech Characteristics TatyanaSineokova(Nizhni Novgorod State Linguistic University, Russia) tns@lunn.ru Corfu, 2011

2. Studies of emotions speech correlatives show: - on phonetic/phonological and lexical levelsthere exists a certain set of language exponentsof a particular emotional state - syntactic level in this respect proves to be irrelevant (for example, such different emotions as delight and anger are often manifested through similar syntactic constructions)

3. Analysis of speech patterns realized in the state of emotional tension shows that syntactic variations dependnot on a definite emotion but on the impact – positive (constructive) or negative (destructive) – the emotion produces on a person’s activity on the whole, including speech-thought processes.

4. Studies in biochemistry, physiology, psychology show that emotional states immediately affecting thinking and speaking activities can be classified into three major types: —dissociation/dissolution/distressexerting negative influence upon thinking and speaking activities; —eustress exerting positive influence upon the activities; — boundary adaptation state between the two which we called searching state.

5. The three types • represent steady physiological states, • are discrete, • can be reliably identified in the course of laboratory biochemical and physiological tests

6. State of eustress consciousness is relatively under control • Searching state boundary zone • State of dissociation minimum level of consciousness

7. The three-term series of emotional states was taken as the extralinguistic constituent of interactive classification aiming at establishing significant correlative links between the psychological state and syntactic speech characteristics and thus testifying prognostic potential of the classification

8. The linguistic constituent of the interactive classification was based on the acknowledgment of the deformed character of emotional syntax. Kernel sentence structure realized in neutral speech undergoes changes under the influence of affective processes.

9. Structure deviations of the first two levels of the classification testify to the affective type of speech upon the whole. It’s the last classification level of primary features which displays correlative links with the three psychological states and displays the prognostic potential of the classification.

10. Characteristics of kernel sentence: • limited number of components including only obligatory syntactic positions; • obligatory character of basic syntactic positions; • fixed order of elements within the communicative type of the sentence; • communicative and syntagmatic independence of the sentence.

11. Deviations from kernel sentence structure can be presented as a three-level hierarchical classification including the highest level of transformations the second level of modifications the third level of primary features

12. Structure of linguistic constituent of the interactive classification I. Level of transformations dichotomous division of non-neutral structures: explicative forms implicative forms II. Level of modifications eight deformations of explicative and implicative constructions: repetition materially excessive elements inversion transposition breaks of potential syntactic units decipher constructions ellipsis isolated structures III. Level of primary features forty primary features singled out within the eight deformations

13. Structure deviations of the first two levels of the classification testify to the affective type of speech upon the whole. It’s the last classification level of primary features which displays correlative links with the three psychological states and displays the prognostic potential of the classification.

14. The informative value of the classification can be estimated on the basis of Boltzmann entropy of choice before and after application of the algorithm of prognosis. When testing a sample of 1000 utterances, initial entropy of 1.6 bits (which corresponds to the choice of one of three equally probable psychological states) was reduced to 0.89 bits. Thus, the results indicate approximately two-fold reduction of the original sample entropy. As uncertainty estimated for entropy uses a logarithmic scale, prognostic potential of the developed classification can be regarded as good enough. Such rare psychological states as the state of dissociation and the searching state are identified in 82% and 70% cases respectively.

15. Research program. Fragment 1.

16. Research program. Fragment 2.

17. Research program. Fragment 3.

18. Some regularities in the use of structural forms in different states were established: diversity, complexity, frequency, dominance and compatibility of features. Presumably, these regularities should be included in the algorithms of identifying signs of emotional speech deviations to distinguish it from other forms of speech deviations and to highlight specific emotional forms.

19. Complexity (number of structural features) of the utterance realized in different states, %

20. All these estimates are "lower estimates" demonstrating the possibility of emotional state prognosis based on the analysis of structural features of the utterance. As the development of optimal prediction algorithm was not included in the objectives of the work, more complex algorithms can significantly improve the outcome prediction.

21. THAHK YOU! Contacts: Tatyana Sineokova (tns@lunn.ru)