Automatic task slots assignment in Hadoop MapReduce
Kun Wang, Juwei Shi, et al.
PACT 2011
In this paper, we present a fast, vocabulary independent, algorithm for spotting words in speech. The algorithm consists of a phone-ngram representation (indexing) stage and a coarse-to-detailed search stage for spotting a word/phone sequence in speech. The phone-ngram representation stage provides a phoneme-level representation of the speech that can be searched efficiently. We present a novel method for phoneme-recognition using a vocabulary prefix tree to guide the creation of the phone-ngram index. The coarse search, consisting of phone-ngram matching, identifies regions of speech as putative word hits. The detailed acoustic match is then conducted only at the putative hits identified in the coarse match. This gives us vocabulary independence and the desired accuracy and speed in wordspotting. Current lattice-based phoneme-matching algorithms are similar to the coarse-match step of our algorithm. We show that our combined algorithm gives a factor of two improvement over the coarse match. The algorithm has wide-ranging use in distributed and pervasive speech recognition applications such as audio-indexing, spoken message retrieval and video-browsing.
Kun Wang, Juwei Shi, et al.
PACT 2011
Paul A. Karger
SOUPS 2006
Graham Mann, Indulis Bernsteins
DIMEA 2007
Jianchang Mao, Patrick J. Flynn, et al.
Computer Vision and Image Understanding