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The <a href="http://cran.r-project.org/web/packages/textcat/index.html"><code>textcat</code></a> package does this. It can detect 74 'languages' (more properly, language/encoding combinations), more with other extensions. Details and examples are in this freely available article: Hornik, K., Mair, P., Rauch, J., Geiger, W., Buchta, C., & Feinerer, I. <a href="http://www.jstatsoft.org/v52/i06/">The textcat Package for n-Gram Based Text Categorization</a> in R. Journal of Statistical Software, 52, 1-17. Here's the abstract: <blockquote> Identifying the language used will typically be the first step in most natural language processing tasks. Among the wide variety of language identification methods discussed in the literature, the ones employing the Cavnar and Trenkle (1994) approach to text categorization based on character n-gram frequencies have been particularly successful. This paper presents the R extension package textcat for n-gram based text categorization which implements both the Cavnar and Trenkle approach as well as a reduced n-gram approach designed to remove redundancies of the original approach. A multi-lingual corpus obtained from the Wikipedia pages available on a selection of topics is used to illustrate the functionality of the package and the performance of the provided language identification methods. </blockquote> And here's one of their examples: <pre><code>library("textcat") textcat(c( "This is an English sentence.", "Das ist ein deutscher Satz.", "Esta es una frase en espa~nol.")) [1] "english" "german" "spanish" </code></pre>
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