Re-ranking Spoken Term Detection with Acoustic Exemplars of Keywords

Publication date: Available online 5 September 2018Source: Speech CommunicationAuthor(s): Van Tung Pham, Haihua Xu, Xiong Xiao, Nancy F. Chen, Eng Siong Chng, Haizhou LiAbstractSpoken term detection (STD) systems rank hypothesized detections by scores, which indicate how confident a hypothesized detection is a true instance of the keyword. Many STD systems rely on automatic speech recognition (ASR) to transcribe the speech content into the lattice representation. In such STD systems, the detection scores are usually estimated as the posterior probabilities of the keyword in the decoding lattices. Such scores may be inaccurate, e.g. due to the imperfect modeling of speech and noise. To improve the ranking of hypothesized detections, we propose to directly utilize the acoustic similarity sco...

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