SPEECHFIND: spoken document retrieval for a national gallery of the spoken word
John H. L. Hansen, Rongqing Huang, Praful Mangalath, Bowen Zhou, Michael S. Seadle, J.R. Deller · 2004
In this study, we discuss a number of issues for audio stream phrase recognition for information retrieval for a new National Gallery of the Spoken Word (NGSW). NGSW is the first largescale repository of its kind, consisting of speeches, news broadcasts, and recordings that are of historical content from the 20 Century. We propose a system diagram and discuss critical tasks associated with effective audio information retrieval that include: advanced audio segmentation, speech recognition model adaptation for acoustic background noise and speaker variability, and natural language processing for text query requests. A number of questions regarding copyright assessment, metadata construction, digital watermarking must also be addressed for a sustainable audio collection of this magnitude. Our experimental online system entitled "SpeechFind" is presented which allows for audio retrieval from a portion of the NGSW corpus. We discuss a number of research challenges to address the overall task of robust phrase searching in unrestricted audio corpora.