Parallel Algorithms for Syllable Recognition in Continuous Speech

Mori, Renato De; Laface, Pietro; Mong, Yu

doi:10.1109/tpami.1985.4767618

Cited by 35 publications

(3 citation statements)

References 11 publications

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“…PE13: VT = (20,t*,20] VF = (1,2,3,4,5,6,7,8,9], PE13 is executed every 20 msecs in the frication interval. It has 16 nodes in the first layer and 10 nodes in the second layer.…”

Section: Organizationmentioning

confidence: 99%

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Programmable execution of multi-layered networks for automatic speech recognition

et al. 1989

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“…PE13: VT = (20,t*,20] VF = (1,2,3,4,5,6,7,8,9], PE13 is executed every 20 msecs in the frication interval. It has 16 nodes in the first layer and 10 nodes in the second layer.…”

Section: Organizationmentioning

confidence: 99%

“…Sonorant segments can be extracted from continuous speech using a procedure described in [5]. Sonorant segments are characterized by narrow-band resonances from which spectral lines as introduced in [lo] are extracted.…”

Section: Organizationmentioning

confidence: 99%

Programmable execution of multi-layered networks for automatic speech recognition

et al. 1989

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“…The signal x(t) is processed in order to obtain a sequence of spectra R. This is done with Fast Fourier Transformation (FFT) but for other projects in our research an ear model is used [7]. Another module extracts a sequence A of acoustic properties like zerocrossing rates and energy contour profiles as described in [8]. Two vectors of acoustic parameters are extracted for every frame, namely M (a vector of 6 MCC) and AM (a vector of 6 DMCC).…”

Section: The Hybrid Speech Codermentioning

confidence: 99%

A hybrid coder for hidden Markov models using a recurrent neural networks

Bengio

Cardin

Mori

et al.

International Conference on Acoustics, Speech, and Signal Processing

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A hybrid coder is introduced for obtaining descriptions of speech patterns, This coder uses popular Vector Quantization (VQ) techniques on melscale cepstral coefficients and their derivatives together with a Recurrent Network (RN) for describing suprasegmental features of speech.The purpose of these features is to focus the search when Hidden Markov Models (HMM) are used for speech unit or word models.Preliminary experiments of speakerindependent connected digit recognition showed that using a hybrid coder based on a RN improved recognition performance.

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Mathematical Models for Speech Technology

Levinson¹

2005

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Parallel Algorithms for Syllable Recognition in Continuous Speech

Cited by 35 publications

References 11 publications

Programmable execution of multi-layered networks for automatic speech recognition

Programmable execution of multi-layered networks for automatic speech recognition

A hybrid coder for hidden Markov models using a recurrent neural networks

Mathematical Models for Speech Technology

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