Chester Palen-Michel


2019

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SARAL: A Low-Resource Cross-Lingual Domain-Focused Information Retrieval System for Effective Rapid Document Triage
Elizabeth Boschee | Joel Barry | Jayadev Billa | Marjorie Freedman | Thamme Gowda | Constantine Lignos | Chester Palen-Michel | Michael Pust | Banriskhem Kayang Khonglah | Srikanth Madikeri | Jonathan May | Scott Miller
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations

With the increasing democratization of electronic media, vast information resources are available in less-frequently-taught languages such as Swahili or Somali. That information, which may be crucially important and not available elsewhere, can be difficult for monolingual English speakers to effectively access. In this paper we present an end-to-end cross-lingual information retrieval (CLIR) and summarization system for low-resource languages that 1) enables English speakers to search foreign language repositories of text and audio using English queries, 2) summarizes the retrieved documents in English with respect to a particular information need, and 3) provides complete transcriptions and translations as needed. The SARAL system achieved the top end-to-end performance in the most recent IARPA MATERIAL CLIR+summarization evaluations. Our demonstration system provides end-to-end open query retrieval and summarization capability, and presents the original source text or audio, speech transcription, and machine translation, for two low resource languages.