| | |
Summary: Automatic Indexing of Audio 1
Fast Caption Alignment for Automatic Indexing of Audio
Allan Knight, University of California, Santa Barbara USA
Kevin Almeroth, University of California, Santa Barbara, USA
Abstract
For large archives of audio media, just as with text archives, indexing is important for allowing
quick and accurate searches. Similar to text archives, audio archives can use text for indexing.
Generating this text requires using transcripts of the spoken portions of the audio. From them, an
alignment can be made that allows users to search for specific content and immediately view the
content at the position where the search terms were spoken. Although previous research has
addressed this issue, the solutions align the transcripts only in real-time or greater. In this paper,
the authors propose AUTOCAP. It is capable of producing accurate audio indexes in faster than
real-time for archived audio and in real-time for live audio. In most cases it takes less than one
quarter the original duration for archived audio. This paper discusses the architecture and
evaluation of the AUTOCAP project as well as two of its applications.
Keywords: Audio Processing; Indexing; Multimedia; Natural Language Processing; Speech
Recognition
Automatic Indexing of Audio 2
Fast Caption Alignment for Automatic Indexing of Audio
Over the past 10 years, automatic speech recognition has become faster, more accurate,
|
