EVOLAEMP

Language Evolution: The Empirical Turn

Coordinatore	EBERHARD KARLS UNIVERSITAET TUEBINGEN    more Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie.
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

#	participant	country	role	EC contrib. [€]
1	EBERHARD KARLS UNIVERSITAET TUEBINGEN  Organization address address: GESCHWISTER-SCHOLL-PLATZ city: TUEBINGEN postcode: 72074 contact info Titolo: Prof. Nome: Friedrich Cognome: Hamm Email: send email Telefono: 4970710000000	DE (TUEBINGEN)	hostInstitution	2˙003˙580.00
2	EBERHARD KARLS UNIVERSITAET TUEBINGEN  Organization address address: GESCHWISTER-SCHOLL-PLATZ city: TUEBINGEN postcode: 72074 contact info Titolo: Prof. Nome: Gerhard Cognome: Jäger Email: send email Telefono: 4970710000000 Fax: 497071000000	DE (TUEBINGEN)	hostInstitution	2˙003˙580.00

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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.'