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Cultural Emergence of Combinatorial Structure in Artificial Language Transmission

Explore impact of semantic content on developing structure in artificial language through signal transmission. Experimentation with symbols and GIFs. Results suggest no significant difference between studies. Further analysis underway.

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Cultural Emergence of Combinatorial Structure in Artificial Language Transmission

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Presentation Transcript

  1. SE367 ProjectDevelopment of Structure in Artificial Language Vidur Kumar Y8560

  2. 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.

  3. 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

  4. 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 • Methodology: • 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 • Analysis: • Error in transmission should decrease FASTER than in Study 1

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

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

  7. Sample of Data 5 • Fidelity increases [distance decreases] across generations • Final analysis pending completion of Data… 7 2 2 1 0

  8. Expected Results • Given current data – • 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

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