This paper presents the final version of the Czech Broadcast Conversation Corpus that will shortly be released at the Linguistic Data Consortium (LDC). The corpus contains 72 recordings of a radio discussion program, which yields about 33 hours of transcribed conversational speech from 128 speakers. The release does not only include verbatim transcripts and speaker information, but also structu...

We present an approach to creating corpora for use in detecting deception in text, including a discussion of the challenges peculiar to this task. Our approach is based on soliciting several types of reviews from writers and was implemented using Amazon Mechanical Turk. We describe the multi-dimensional corpus of reviews built using this approach, available free of charge from LDC as the Boulde...

Progress in human language technology requires increasing amounts of data and annotation in a growing variety of languages. Research in Named Entity extraction is no exception. Linguistic Data Consortium is creating annotated corpora to support information extraction in English, Chinese, Arabic, and other languages for a variety of US Governmentsponsored programs. This paper covers the scope of...

The interest in syntactically-annotated data for improving machine translation quality has spurred the growing demand for parallel aligned treebank data. To meet this demand, the Linguistic Data Consortium (LDC) has created large volume, multi-lingual and multi-level aligned treebank corpora by aligning and integrating existing treebank annotation resources. Such corpora are more useful when th...

Linguistic Resources for Text Planning M a r i e W . M e t e e r BBN Systems & Technologies Corporation 10 Moulton Street Cambridge, Massachusetts 02138 [email protected]

We present an automated method for estimating the difficulty of spoken texts for use in generating items that assess non-native learners’ listening proficiency. We collected information on the perceived difficulty of listening to various English monologue speech samples using a Likert-scale questionnaire distributed to 15 non-native English learners. We averaged the overall rating provided by t...