1 Assessing Document and Sentence Readability in Less Resourced Languages and across Textual Genres Felice Dell’Orletta, Simonetta Montemagni and Giulia Venturi Istituto di Linguistica Computazionale “Antonio Zampolli” (ILC–CNR) via G. Moruzzi, 1 – Pisa (Italy) {felice.dellorletta,simonetta.montemagni,giulia.venturi}@ilc.cnr.it Abstract In this paper, we tackle three open issues of the automatic readability assessment literature, namely: the evaluation of text readability in less resourced languages, with respect to sentences (as opposed to documents) as well as across textual genres. Different solutions to these issues have been tested by using and specialising READ–IT, the first advanced readability assessment tool for what concerns Italian, which combines traditional raw text features with lexical, morpho-syntactic and syntactic information. In READ–IT readability assessment is carried out with respect to both documents and sentences where the latter represents an important novelty of the proposed approach: READ–IT shows a high accuracy in the document classification task and promising results in the sentence classification scenario. By comparing the results of two versions of READ-IT, adopting a classification- vs ranking- based approach, we also show that readability assessment is strongly influenced by textual genre and for this reason a genre–oriented notion of readability is needed. With classification–based approaches, reliable results can only be achieved with genre–specific models: since this is far from being a workable solution, especially for less–resourced languages, a new ranking method for readability assessment is proposed, based on the notion of distance. Key words Classification; Less Resourced Languages; Multi-Level Linguistic Annotation; Ranking; Readability; Textual Genres