Jennifer Garland


2014

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Collecting Natural SMS and Chat Conversations in Multiple Languages: The BOLT Phase 2 Corpus
Zhiyi Song | Stephanie Strassel | Haejoong Lee | Kevin Walker | Jonathan Wright | Jennifer Garland | Dana Fore | Brian Gainor | Preston Cabe | Thomas Thomas | Brendan Callahan | Ann Sawyer
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

The DARPA BOLT Program develops systems capable of allowing English speakers to retrieve and understand information from informal foreign language genres. Phase 2 of the program required large volumes of naturally occurring informal text (SMS) and chat messages from individual users in multiple languages to support evaluation of machine translation systems. We describe the design and implementation of a robust collection system capable of capturing both live and archived SMS and chat conversations from willing participants. We also discuss the challenges recruitment at a time when potential participants have acute and growing concerns about their personal privacy in the realm of digital communication, and we outline the techniques adopted to confront those challenges. Finally, we review the properties of the resulting BOLT Phase 2 Corpus, which comprises over 6.5 million words of naturally-occurring chat and SMS in English, Chinese and Egyptian Arabic.

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Incorporating Alternate Translations into English Translation Treebank
Ann Bies | Justin Mott | Seth Kulick | Jennifer Garland | Colin Warner
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

New annotation guidelines and new processing methods were developed to accommodate English treebank annotation of a parallel English/Chinese corpus of web data that includes alternate English translations (one fluent, one literal) of expressions that are idiomatic in the Chinese source. In previous machine translation programs, alternate translations of idiomatic expressions had been present in untreebanked data only, but due to the high frequency of such expressions in informal genres such as discussion forums, machine translation system developers requested that alternatives be added to the treebanked data as well. In consultation with machine translation researchers, we chose a pragmatic approach of syntactically annotating only the fluent translation, while retaining the alternate literal translation as a segregated node in the tree. Since the literal translation alternates are often incompatible with English syntax, this approach allows us to create fluent trees without losing information. This resource is expected to support machine translation efforts, and the flexibility provided by the alternate translations is an enhancement to the treebank for this purpose.