BOLT Egyptian Arabic-English Word Alignment -- Conversational Telephone Speech Training (LDC2020T05)
Domain:
natural language processingRecord type:
Introduction
BOLT Egyptian Arabic-English Word Alignment -- Conversational Telephone Speech Training was developed by the Linguistic Data Consortium (LDC) and consists of 153,171 words of Egyptian Arabic and English parallel text enhanced with linguistic tags to indicate word relations.
The DARPA BOLT (Broad Operational Language Translation) program developed machine translation and information retrieval for less formal genres, focusing particularly on user-generated content. LDC supported the BOLT program by collecting informal data sources -- discussion forums, text messaging and chat -- in Chinese, Egyptian Arabic and English. The collected data was translated and annotated for various tasks including word alignment, treebanking, propbanking and co-reference.
Data
The source data in this release consists of transcripts of Egyptian Arabic conversational telephone speech (CTS) from LDC's CALLHOME and CALLFRIEND collections (LDC97S45, LDC97T19, LDC2002S37, LDC2002T38, LDC96S49) that were translated into English by professional translation agencies and annotated for the word alignment task.
The BOLT word alignment task was built on treebank annotation. Specifically, Egyptian Arabic source tree tokens were automatically extracted from tree files in LDC's BOLT Egyptian Arabic Treebank. Those tree files had been tagged for part-of-speech and syntactically annotated. That data was then aligned and annotated for the word alignment task.
The data profile broken down by character tokens, tree tokens and segments appears below:
Language Genre Files Words Tree-tokens Segments
Egyptian Arabic CTS 176 153,171 215,896 20,010