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Record W3035239247 · doi:10.5539/ijel.v10n4p184

The Experimental-Phonetic Analyses of the Discourse Intonation in the English and Azerbaijan Languages

2020· article· en· W3035239247 on OpenAlex
Sahila Baghir Gizi Mustafayeva

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of English Linguistics · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCultural, Linguistic, Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIntonation (linguistics)ConversationLinguisticsPoint (geometry)PsychologySubject (documents)Object (grammar)Computer scienceMathematicsPhilosophy

Abstract

fetched live from OpenAlex

The article deals with the experimental-phonetic analyses of the discourse intonation in the English and Azerbaijan languages. Having researched the article, it becomes clear that discourse intonation (DI) is an approach to the teaching and analysis of everyday speech. The characteristics of intonation components in the formation of discourse have been touched upon in the article. The intonation is mentioned to be one of the main means in the formation of the discourse. It is a known fact that speech styles can be characterized by their lexical, syntactic and phonetic features. The attention is drawn to the distinguishing points of the speech of the people having various professions such as the speech styles of a teacher and a driver should be different not only from the lexical point of view but also from the phonetic point of view. During the conversation, one can come across some nuances of the speaker’s intellectual level, life experience and social status. It is also important to remember that the subject of the conversation is meant to be an important factor too. The object of the conversation ensures the stylistic formation of the idea. The importance of the experiment has been taken into a special consideration in the article as well. The opinion of academician L. V. Sherba that stresses the importance of the experiment has been analyzed by the author. The factors that are needed to be followed by while carrying out the language facts have been fulfilled in the article. The author tries to prove that DI is concerned with the speakers’ moment-by-moment context-referenced choices. It recognizes four systems of speaker’s choice: prominence, tone, melodicy, and termination. The discourse samples having been chosen for the experiment are fulfilled by using various sentence types. Besides, the inside structure of the sentences and their lexical contents are also taken into account in the article. Some discourse samples have been chosen in the comparable languages to be experimented in order to distinguish the intonation nature of the discourse. The experiment has been carried out by using the program “Praat”. It is noteworthy to mention that the program “Praat” is known to be a computer operation used to analyze speech sounds.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.137
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.340
Threshold uncertainty score0.870

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.137
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.391
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it