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IEEE Transactions on Acoustics Speech and Signal Processing is a peer-reviewed journal published by IEEE, covering Digital Filter Design and Implementation, Advanced Adaptive Filtering Techniques, Image and Signal Denoising Methods.
| Publisher | IEEE |
|---|---|
| Reference style | Numbered (IEEE) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, and C. Lee, "A representative article title," IEEE Transactions on Acoustics Speech and Signal Processing, vol. 12, no. 3, pp. 45–58, 2023.
Formats any DOI in IEEE Transactions on Acoustics Speech and Signal Processing style. No sign-up. |
| Publishes research in | Digital Filter Design and Implementation Advanced Adaptive Filtering Techniques Image and Signal Denoising Methods Speech and Audio Processing Blind Source Separation Techniques |
| ISSN | 0096-3518 |
| h-index | 233 |
| i10-index | 2,034 |
| Total citations | 275,528 |
| Top institutions publishing here | Massachusetts Institute of Technology |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
An approach to the general problem of signal parameter estimation is described. The algorithm differs from its predecessor in that a total least-squares rather than a standard least-squares criterion is used. Although discussed in the context of direction-of-arrival estimation, ESPRIT can be applied to a wide variety of problems including accurate detection and estimation of…
This paper reports on an optimum dynamic progxamming (DP) based time-normalization algorithm for spoken word recognition. First, a general principle of time-normalization is given using time-warping function. Then, two time-normalized distance definitions, called symmetric and asymmetric forms, are derived from the principle. These two forms are compared with each other through theoretical discussions and experimental…
Several parametric representations of the acoustic signal were compared with regard to word recognition performance in a syllable-oriented continuous speech recognition system. The vocabulary included many phonetically similar monosyllabic words, therefore the emphasis was on the ability to retain phonetically significant acoustic information in the face of syntactic and duration variations. For each parameter set…
A stand-alone noise suppression algorithm is presented for reducing the spectral effects of acoustically added noise in speech. Effective performance of digital speech processors operating in practical environments may require suppression of noise from the digital wave-form. Spectral subtraction offers a computationally efficient, processor-independent approach to effective digital speech analysis. The method, requiring about the…
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