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David Ardell, Noelle Anderson, Bodo Winter
Rie Asano, Edward Ruoyang Shi
Mark Atkinson, Kenny Smith, Simon Kirby
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Christian Bentz
Aleksandrs Berdicevskis, Hanne Eckhoff
Richard A. Blythe, Alistair H. Jones, Jessica Renton
Cedric Boeckx, Constantina Theofanopoulou, Antonio Benítez-Burraco
Megan Broadway, Jamie Klaus, Billie Serafin, Heidi Lyn
Jon W. Carr, Kenny Smith, Hannah Cornish, Simon Kirby
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Katie Collier, Andrew N. Radford, Balthasar Bickel, Marta B. Manser, Simon W. Townsend
Jennifer Culbertson, Simon Kirby, Marieke Schouwstra
Christine Cuskley, Vittorio Loreto
Christine Cuskley, Bernardo Monechi, Pietro Gravino, Vittorio Loreto
Dan Dediu, Scott Moisik
Sabrina Engesser, Amanda R. Ridley, Simon W. Townsend
Dankmar Enke, Roland Mühlenbernd, Igor Yanovich
Kerem Eryilmaz, Hannah Little, Bart de Boer
Nicolas Fay, Shane Rogers
Maryia Fedzechkina, Becky Chu, T. Florian Jaeger, John Trueswell
Olga Feher, Kenny Smith, Elizabeth Wonnacott, Nikolaus Ritt
Piera Filippi, Sebastian Ocklenburg, Daniel Liu Bowling, Larissa Heege, Albert Newen, Onur Güntürkün, Bart de Boer
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Molly Lewis, Michael C. Frank
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Hannah Little, Kerem Eryılmaz, Bart de Boer
Hannah Little, Kerem Eryılmaz, Bart de Boer
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Jérôme Michaud
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Terry Regier, Alexandra Carstensen, Charles Kemp
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Catriona Silvey, Christos Christodoulopoulos
Katie Slocombe, Stuart Watson, Anne Schel, Claudia Wilke, Emma Wallace, Leveda Cheng, Victoria West, Simon Townsend
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Simon Townsend, Andrew Russell, Sabrina Engesser
Francesca Tria, Vittorio Loreto, Vito Servedio, S. Mufwene Salikoko
Anu Vastenius, Jordan Zlatev, Joost Van de Weijer
Tessa Verhoef, Carol Padden, Simon Kirby
Slawomir Wacewicz, Przemyslaw Zywiczynski, Arkadiusz Jasinski
Bodo Winter, David Ardell
Bodo Winter, Lynn Perry, Marcus Perlman, Gary Lupyan
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Eva Zehentner, Andreas Baumann, Nikolaus Ritt, Christina Prömer
Keywords: specializations for speech learning, distributional learning, category learning, continuous signals, comparing modalities
Short description: Learning bimodal distributions of auditory, visual, and tactile signals: is category learning specialized for speech?
Abstract:
The evolution of linguistic cognition is a notoriously difficult problem: as all learning mechanisms are intertwined with human development and behavior, it is hard to tease apart which aspects of language are the result of cultural processes and which are evolved cognitive traits (De Boer, 2015). We explore whether humans have specializations related to language, and specifically, whether statistical learning of categories is specialized for language-like signals. While it is well-known that statistical learning is not restricted to language learning, the way the mechanism operates in different domains may not be the same, and may be affected by perceptual and cognitive constraints (Conway & Christiansen, 2005).
We present an experiment in which participants learn, categorize, and reproduce signals in the acoustic, visual, and tactile modalities. Participants are trained on bimodal distributions of tones, images and buzzes with some variation in duration, resulting in a `long' and `short' category (Maye et al., 2002). After training, participants rate individual signals on a 6 point scale from `definitely short' to `definitely long'. The production task consists of creating 3 signals for both categories by pressing the mouse button. The signal is presented as long as the button is pressed. If there is indeed a specialization for learning language-like signals, then we expect that participants reveal: a) more certainty in the categorization task in the auditory and visual conditions, and b) better estimation of the peaks in the distributions, resulting in more reliable reproductions of the categories in the auditory and visual conditions. Alternatively, in normal hearing adults there may be a linguistic training effect, for instance from distinctions between long and short vowels in their native language, in which case better performance in the auditory condition compared to the other conditions is expected, following earlier perception studies (Jones et al., 2009).
A within subjects design provided us with categorization and production data from 29 participants in all modalities. Results from a logistic regression reveal three interesting trends. First, statistical learning of categories and (reliably) reproducing them is possible in all domains, including the tactile modality. Second, and most importantly, the categorization and production processes are remarkably similar in the tactile and auditory domains (odds ratios 0.99 and 1.10; 95\% confidence intervals 0.84-1.15 and 0.94-1.28, respectively), but not in the visual domain (OR = 1.30; CIs = 1.12-1.53), suggesting that there is no cognitive specialization for learning language-like signals, nor that there is an effect from previous language experience. Finally, comparing the categorization and production data reveals an interesting tension: on the one hand, we demonstrate that across all three modalities participants were able to induce representations of distinct categories that respect the statistics of the training distributions. On the other hand, we consistently find more variation in duration among participants' productions than was present in the training distributions. This pattern of variation differs between modalities, with more variation in the visual modality. We fitted a Bayesian model of inference for Gaussian distributions to the data in order to investigate whether this variation reflects a meaningful component of the learning process, and to provide a quantitative characterization of the pattern of differences in how participants formed categories in this experiment. The model correctly predicts the overall pattern of categorization behaviour that we find in the empirical data.
Our study further explores the extent to which statistical learning is domain general, as it is becoming increasingly clear that we cannot approach it as a unitary mechanism (e.g. Frost et al., 2015). Teasing apart differences between modalities will help us find out how the perceptional biases of each modality potentially affect these learning mechanisms, which is necessary for understanding whether certain forms of learning are specialized for language.
Citation:
van der Ham S., Thompson B. and de Boer B. (2016). Catergory Learning In Audition, Touch, And Vision. In S.G. Roberts, C. Cuskley, L. McCrohon, L. Barceló-Coblijn, O. Fehér & T. Verhoef (eds.) The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11). Available online: http://evolang.org/neworleans/papers/38.html