Bolivian Quechua (Quechuan)
Quechua is the last case study discussed in the paper, and the one that most clearly highlights the problem of the nature of the learning data. As described in the paper, the simulations on word corpora fail in various ways to arrive at the posited (uncontroversial) inventory of affricates. The reason is that the phonotactics and morphology of Quechua conspire to inflate the frequencies of certain clusters, diluting the frequencies of affricates. Reasonable-looking results arrive only when the learner is trained on more abstract data: roots or a morpheme list. Quechua is also a case where we tried to decompose aspirated and ejective plosives into more primitive parts. The learner does not find these segments when trained on words.
Simulation data at a glance
Click on simulation name to view additional simulation details.
|Simulation name||Initial state Learning Data||Initial state features|
Simulation details for Quechua words broad
This word list was compiled from an online Quechua newspaper. See Gouskova and Gallagher 2019 for further details.
Summary of iterations:
|Iteration||Learning Data produced||Features produced||Inseparability||New Segments added||Segments removed|
|1||LearningData.txt||Features.txt||[download] [view]||tʃ||ŋ, ɴ|
|2||LearningData.txt||Features.txt||[download] [view]||tʃ', sq, ɲtʃ, jk||ʃ'|
|4||LearningData.txt||Features.txt||[download] [view]||tʃʰ, nt, rq||ʃʰ|
|6||LearningData.txt||Features.txt||[download] [view]||xt, mp, jt||None|
|7||LearningData.txt||Features.txt||[download] [view]||sp, ʎp'||None|
|10||No new learning data||No new features||[download] [view]||None||None|