Simulated distributional learning in deep Boltzmann machines leads to the emergence of discrete categories
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| Publication date | 2019 |
| Book title | Proceedings of the 19th International Congress of Phonetic Sciences, Melbourne, Australia 2019 |
| Book subtitle | ICPhS2019 : 5-9 August 2019, Melbourne Australia |
| ISBN (electronic) |
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| Event | International Congress of Phonetic Sciences |
| Pages (from-to) | 1520-1524 |
| Number of pages | 5 |
| Publisher | Canberra: Australasian Speech Science and Technology Association Inc |
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| Abstract | There is a potential close correspondence between multi-level linguistic theories and bidirectional deep artificial neural networks. This paper shows that in a deep Boltzmann machine, simulated distributional learning of spectral content leads to the emergence of appropriate categorical behaviour, both along a one-dimensional continuum (three sibilant places) and along a two-dimensional continuum (five vowels). |
| Document type | Conference contribution |
| Language | English |
| Other links | https://www.icphs2019.org/ |
| Downloads |
2019-icphs-Boersma
(Final published version)
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