1. SE367 Project Development of Structure in Artificial Language
Vidur Kumar
Y8560

2. 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.

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
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

5. [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 ]

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

8. 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