SE367 Project Development of Structure in Artificial Language

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Presentation transcript:

SE367 Project Development of Structure in Artificial Language Vidur Kumar Y8560

Q. Will semantic content improve/effect development? Background Study – Artificial (unfamiliar) signal transmission in iterative learning [whistling sounds] Results – Structure develops across generations Q. Will semantic content improve/effect development? Tessa Verhoef, Simon Kirby & Carol Padden – “Cultural emergence of combinatorial structure in an artificial whistled language”. CogSci2011.

Hypothesis Semantic content – will allow for FASTER development of structure in artificial language transmission. Tools “Symbols” instead of “sound” [ease of experimentation] Semantic content via – GIFs

Experimental design Study 1 [3x (6-7 participants)] Non-semantic signal transmission Methodology: Input symbols to nth participant [random symbols for n = 1] [5-10sec] Use output of nth participant as (n+1)th participant’s input Analysis: Error in transmission decreases with generations Study 2 [3x (6-7 participants)] Semantic communication with artificial language Train nth participant on random symbols against ‘seen’ GIFs [1 time] Test of ‘unseen’ GIFs [different combination of colour & motion] Use output of nth participant as (n+1)th participant’s training set Error in transmission should decrease FASTER than in Study 1

[Sample of Symbols used, and some results of Study 1 ] The Problem Non-quantifiable fidelity [Sample of Symbols used, and some results of Study 1 ]

Re-evaluation of Experimental design Quantifiable symbols Every non-identical square = +1 diff. unit Exact estimate of fidelity between generations Restarted data collection…

Sample of Data 5 Fidelity increases [distance decreases] across generations Final analysis pending completion of Data… 7 2 2 1

Thank You Expected Results Given current data – Likely inference – No significant difference between Study 1 and Study 2 results Perhaps a short-coming of : Complexity of Artificial Language Fewer number of generations in iterative learning Variation in semantic content Likely inference – ease-of-transmission – more dominant in stabilizing complex artificial languages Semantic-mapping – does not significantly affect stabilization of complex artificial languages (random signal systems) Thank You