LOTUS-BN: A Thai broadcast news corpus and its research applications

Abstract

This paper describes the design and construction of the LOTUS-BN corpus, a Thai television broadcast news corpus. In addition to audio recordings and their transcription, this corpus also includes a detailed annotation of many interesting characteristics of broadcast news data such as acoustic condition, overlapping speech, news topic and named entity. The LOTUS-BN is still an ongoing project with the goal of collecting 100 hours of speech. We report initial statistics analyzed from 60 hours of speech which show that the LOTUS-BN corpus has a rich vocabulary of approximately 26,000 words with one third of them are named entities. Thus, this corpus is a good resource for developing an LVCSR system and investigating on named entity detection and recognition in addition to broadcast news related applications. Research applications on these topics are also discussed.