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This paper describes the TBNR system, which features at many state-of-the-art technologies of speech recognition, covering the decoder, acoustic modeling, speech recognition features, and etc. By integrating these technologies, several optimizations have been performed to utilize multi-processors resources. Along with models in several typical languages, these systems could be used at once for several...
In this paper, we present our initial efforts in the task of Automatically Synchronizing live spoken Utterances with their Transcripts (textual contents) (ASUT) when the texts are known. We treat it as a online speech-text alignment problem. And it is further simplified into the problem of on-the-fly detecting of the end time of a spoken utterance given its textual content. A general framework called...
This paper presents an improvement for confidence measure estimation as posterior probabilities on lattices in speech recognition. An observation is presented that nontarget regions, i.e. non-speech part of a spoken utterance, of different lengths may lead to different levels of over optimistic confidence measures. This may be problematic in obtaining a consistent rejection performance at the same...
This paper examines the system combination issue for syllable-confusion-network (SCN)-based Chinese spoken term detection (STD). System combination for STD usually leads to improvements in accuracy but suffers from increased index size or complicated index structure. This paper explores methods for efficient combination of a word-based system and a syllable-based system while keeping the compactness...
This paper details our subword confusion network based approach for Mandarin spoken term detection. As well as the system description, two approaches are presented for improvement of our baseline system. To reduce the inherent high recognition error of the subword decoding system due to its weak language model constraints, the subword confusion network is proposed to be generated from the word decoding...
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