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This paper presents our efforts in automatically synchronizing spoken utterances with their transcripts (textual contents) (ASUT), where the speech is a live stream and its corresponding transcripts are known. This task is first simplified to the problem of online detecting the end times of spoken utterances and then a solution based on a novel frame-synchronous likelihood ratio test (FSLRT) procedure...
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...
A modified joint source-channel decoding (JSCD) algorithm based on low-density parity-check (LDPC) codes and hidden Markov estimation has been presented and extended to applying over Rayleigh fading channels. The proposed algorithm utilizes the source residual redundancy lack of any priori information of the source parameters, and the modifications employ the self-checking and convergence mechanisms...
A modified joint source channel decoding (JSCD) algorithm based on low-density parity-check (LDPC) coding and hidden Markov estimation is proposed to employ the self-checking mechanism of LDPC codes in adjusting the error probability p of the hidden Markov model (HMM) and the JSCD scheme utilizes the source residual redundancy while no priori information of the source parameters is available. We also...
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