Language Evolution: The Empirical Turn

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."

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.

• humanities languages and literature linguistics
• humanities history and archaeology history
• natural sciences computer and information sciences data science natural language processing
• natural sciences computer and information sciences artificial intelligence machine learning
• social sciences psychology psycholinguistics

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

• 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)

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

• ERC-AG-SH4 - ERC Advanced Grant - The Human Mind and its complexity

Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

ERC-2012-ADG_20120411
See other projects for this call

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

ERC-AG - ERC Advanced Grant

Host institution

Beneficiaries (1)