EVOLAEMP
Language Evolution: The Empirical Turn
| Coordinatore | EBERHARD KARLS UNIVERSITAET TUEBINGEN
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| Nazionalità Coordinatore | Germany [DE] |
| Totale costo | 2˙003˙580 € |
| EC contributo | 2˙003˙580 € |
| Programma | FP7-IDEAS-ERC
Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | ERC-2012-ADG_20120411 |
| Funding Scheme | ERC-AG |
| Anno di inizio | 2013 |
| Periodo (anno-mese-giorno) | 2013-04-01 - 2018-03-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
EBERHARD KARLS UNIVERSITAET TUEBINGEN
Organization address
address: GESCHWISTER-SCHOLL-PLATZ contact info |
DE (TUEBINGEN) | hostInstitution | 2˙003˙580.00 |
| 2 |
EBERHARD KARLS UNIVERSITAET TUEBINGEN
Organization address
address: GESCHWISTER-SCHOLL-PLATZ contact info |
DE (TUEBINGEN) | hostInstitution | 2˙003˙580.00 |
Mappa
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Obiettivo del progetto (Objective)
'This proposal describes a highly interdisciplinary approach to the empirical study of cultural language evolution. It draws on ideas and methods from *historical linguistics and typology*, *natural language processing*, *biology*, *bioinformatics*, *computer science*, and *statistics*.
The computer aided study of cultural language evolution has seen a tremendous upturn over the past fifteen years. This comprises both model-driven approaches - studying the consequences of design assumptions regarding language production, comprehension, and learning for their long-term population-wide consequences - and data-driven approaches that employ algorithmic techniques from bioinformatics to recover otherwise inaccessible information about language history. At the current junction, the field faces two challenges:
- The specifics of language evolution - which includes parallels with but also key differences to biological evolution - require central attention.
- Model-driven and data-driven approaches need to inform each other to achieve explanatory power and to assess the statistical significance of the findings.
The project will establish a radically data-oriented framework for the study of language evolution. This includes three aspects:
- replacing the off-the-shelf tools from bioinformatics that are currently in use in computational language classification by linguistically informed algorithms, esp. *multiple sequence alignment techniques*,
- identifying characteristic traits of language evolution via *exploratory data analysis*, guided by the theory of *complex systems* and employing cutting-edge methods from *machine learning* such as *kernel methods* and *causal inference*, and
- developing, implementing and testing models of language evolution that correctly predict the *statistical fingerprints of language evolution*, i.e. pay sufficient attention to the domain specific features of language evolution that have no counterpart in biological evolution.'