Image Processing Filters for Line Detection-Based Spoken Term Detection

Spoken term detection (STD) from oral presentations is addressed. Specifically, we regard STD as a line detection problem in an image file, in which each pixel holds a syllabledistance between query term and automatic speech recognition (ASR) results. Since such kind of image file essentially includes ASR errors, line detection in noisy image should be investigated. In this paper, we propose line detection-oriented image processing filters for STD. We achieved 0.39 of F-measure for low frequency term (out of vocabulary term in ASR system) detection task, and 0.69 of F-measure for known term (invocabulary term in ASR system) detection task.