Recursive methods for estimating multiple missing values of a multivariate stationary process

Bondon, Pascal; Ruiz, Daren; Gallego, A R Ramón

doi:10.1109/icassp.1998.681699

Cited by 1 publication

(2 citation statements)

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“…We have confirmed experimentally that, if we can use the data of more than about 2 s of data, we can obtain sufficiently converged LP coefficients, and the algorithm performance become relatively stable. We employed the Levinson-Durbin algorithm for single-channel long-term multi-step LP [21], and the class of Schur's algorithm for multichannel long-term multistep LP [21], [28]- [30] to calculate the prediction coefficients efficiently. These fast algorithms enable us to run the whole process at a real-time factor of less than 1, for example, on the Intel Pentium IV 3.4-GHz processor used in our experiments.…”

Section: ) Parameters For Dereverberationmentioning

confidence: 99%

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Suppression of Late Reverberation Effect on Speech Signal Using Long-Term Multiple-step Linear Prediction

Kinoshita

Delcroix

Nakatani

et al. 2009

IEEE Trans. Audio Speech Lang. Process.

162

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Abstract-A speech signal captured by a distant microphone is generally smeared by reverberation, which severely degrades automatic speech recognition (ASR) performance. One way to solve this problem is to dereverberate the observed signal prior to ASR. In this paper, a room impulse response is assumed to consist of three parts: a direct-path response, early reflections and late reverberations. Since late reverberations are known to be a major cause of ASR performance degradation, this paper focuses on dealing with the effect of late reverberations. The proposed method first estimates the late reverberations using long-term multi-step linear prediction, and then reduces the late reverberation effect by employing spectral subtraction. The algorithm provided good dereverberation with training data corresponding to the duration of one speech utterance, in our case, less than 6 s. This paper describes the proposed framework for both single-channel and multichannel scenarios. Experimental results showed substantial improvements in ASR performance with real recordings under severe reverberant conditions.

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Section: ) Parameters For Dereverberationmentioning

confidence: 99%

“…Now, can be rewritten as (27) where Note that, (25) can be efficiently solved by, for example, the class of Schur's algorithm, which is able to determine a least square solution for general block-Toeplitz matrix equations [21], [28]- [30].…”

Section: Appendix III Estimation Of Pre-whitening Filtermentioning

confidence: 99%