ITERATED LEARNING OF SOUND SYSTEMS AND THE EMERGENCE OF TONE CATEGORIES

Abstract

In this abstract we investigate whether emerging sets of signals in cultural evolution experiments show similar structural tendencies as the world’s tone languages. An iterated learning experiment (Kirby, Cornish, & Smith, 2008) was conducted with human participants. The universal phonetic tendencies of tones in human language are relatively well-understood. Following Maddieson (1978), linguistic tones can be level (i.e. only one pitch level), simple contours (two pitch levels) or complex (more than two pitch levels). For instance Mandarin Chinese of Beijing has a high tone, a rising tone, a falling tone and a falling-rising tone and therefore has all three types of tones. Level tones tend to be much more prevalent than contour tones, while there is a simple implicational hierarchy for the different types of tones. If a language has complex contour tones it also has simple contour tones. If it has simple contour tones it also has level contour tones. In short, there seems to be a tendency favoring less complex contours. The experiment was conducted as part of Science Livea, in museum Nemo in Amsterdam. Participants learned and reproduced sets of sounds, similar as in Verhoef, Kirby, and Padden (2011), but the signals were produced with the use of a mouse in a virtual synthesizer-interface on the computer. By pressing the mouse inside a horizontal bar and moving the cursor left and right, the pitch was manipulated. The sound stopped when the mouse was released, therefore a signal could not contain any silent parts, as opposed to the whistled signals used by Verhoef et al. (2011). The output produced by one participant was used as the input for the next, following the design of Kirby et al. (2008). Twelve chains were created with twelve participants in each. The signal sets consisted of 8 signals (two different initial sets were used, each used for 6 chains)