Results 271 to 280 of about 6,722,896 (329)

On the automatic segmentation of speech signals

ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
For large vocabulary and continuous speech recognition, the sub-word-unit-based approach is a viable alternative to the whole-word-unit-based approach. For preparing a large inventory of subword units, an automatic segmentation is preferrable to manual segmentation as it substantially reduces the work associated with the generation of templates and ...
Torbjørn Svendsen, Frank K. Soong
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EEG signal classification of imagined speech based on Riemannian distance of correntropy spectral density

Biomedical Signal Processing and Control, 2020
Several current brain–computer interface (BCI) systems are based on imagined speech. This means that these systems are controlled only by thinking about a speech without verbally expressing it. Imagined speech recognition using electroencephalogram (EEG)
M. A. Bakhshali, M. Khademi, A. Ebrahimi-Moghadam, S. Moghimi   +3 more
semanticscholar   +1 more source

Digital Representations of Speech Signals

Proceedings of the IEEE, 1975
This paper presents several digital signal processing methods for representing speech. Included among the representations are simple waveform coding methods; time domain techniques; frequency domain representations; nonlinear or homomorphic methods; and finaIly linear predictive coding techniques.
R.W. Schafer, L.R. Rabiner
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Speech Processing for Digital Home Assistants: Combining signal processing with deep-learning techniques

IEEE Signal Processing Magazine, 2019
Once a popular theme of futuristic science fiction or far-fetched technology forecasts, digital home assistants with a spoken language interface have become a ubiquitous commodity today. This success has been made possible by major advancements in signal
R. Haeb-Umbach, Shinji Watanabe, T. Nakatani, M. Bacchiani, Björn Hoffmeister, M. Seltzer, H. Zen, M. Souden   +7 more
semanticscholar   +1 more source

Characterization of attractors in speech signals

Biosystems, 1997
It is shown that speech signals can have attractors with fractal dimension. A method for estimating this dimension is given. The existence of this attractor suggests that statistical models for speech may be inappropriate. Moreover, the dimension of this attractor is a lower bound on the order of a linear prediction model.
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An initial segmentation of the speech signal

ICASSP '82. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
An algorithm the aim of which is detection of fundamental classes of the speech signal of the Polish language is described. This algorithm has been designed so as it can detect quickly and at small expense as many classes as possible. Five classes are calculated at present using the following parameters : distances between zero up-crossings, signal ...
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Signal Preprocessing for Speech Recognition

Automation and Remote Control, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Chaotic encryption of speech signals

International Journal of Speech Technology, 2011
This paper introduces a speech encryption approach, which is based on permutation of speech segments using chaotic Baker map and substitution using masks in both time and transform domains. Two parameters are extracted from the main key used in the generation of mask.
Emad Mosa, Nagy Wadie Messiha, Osama Zahran, Fathi E. Abd El-Samie   +3 more
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Adaptive Sampling of Speech Signals

IEEE Transactions on Communications, 1974
The present work gives a proposed method of sampling speech signals with a nonuniform sampling rate according to the magnitude of the slope of the signal, provided that the average sampling rate satisfies Shannon's requirements. With this proposed method, the quality of the reconstructed speech signal is improved.
Abd El-Samie Mostafa, Mohsen M. T. El-Hagry   +1 more
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Multichannel Signal Processing With Deep Neural Networks for Automatic Speech Recognition

IEEE/ACM Transactions on Audio Speech and Language Processing, 2017
Multichannel automatic speech recognition (ASR) systems commonly separate speech enhancement, including localization, beamforming, and postfiltering, from acoustic modeling.
Tara N. Sainath, Ron J. Weiss, K. Wilson, Bo Li, A. Narayanan, Ehsan Variani, M. Bacchiani, Izhak Shafran, A. Senior, K. K. Chin, Ananya Misra, Chanwoo Kim   +11 more
semanticscholar   +1 more source