Results 71 to 80 of about 545,669 (204)
Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices [PDF]
, 2016 In recent years, deep neural networks (DNN) have demonstrated significant business impact in large scale analysis and classification tasks such as speech recognition, visual object detection, pattern extraction, etc.
Gokmen, Tayfun, Vlasov, Yurii
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Hidden Markov Models for Spatio-Temporal Pattern Recognition and Image Segmentation [PDF]
, 2003 Time and again hidden Markov models have been demonstrated to be highly effective in one-dimensional pattern recognition and classification problems such as speech recognition.
Lovell, Brian C.
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Frontiers in Neuroscience, 2014 Knowledge of how executive functions relate to preferred hearing aid (HA) processing is sparse and seemingly inconsistent with related knowledge for speech recognition outcomes. This study thus aimed to find out if (1) performance on a measure of reading
Tobias eNeher
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The speech signal segmentation algorithm using pitch synchronous analysis
Open Computer Science, 2017 Parameterization of the speech signal using the algorithms of analysis synchronized with the pitch frequency is discussed. Speech parameterization is performed by the average number of zero transitions function and the signal energy function ...
Amirgaliyev Yedilkhan +2 more
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Speech as a pilot input medium [PDF]
The speech recognition system under development is a trainable pattern classifier based on a maximum-likelihood technique. An adjustable uncertainty threshold allows the rejection of borderline cases for which the probability of misclassification is high.
Coler, C. R., Plummer, R. P.
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, 2018 In recent days, Artificial Neural Network (ANN) can be applied to a vast majority of fields including business, medicine, engineering, etc. The most popular areas where ANN is employed nowadays are pattern and sequence recognition, novelty detection ...
Arif, Rezoana Bente +3 more
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Feature selection for emotion recognition in speech: a comparative study of filter and wrapper methods [PDF]
PeerJ Computer ScienceFeature selection is essential for enhancing the performance and reducing the complexity of speech emotion recognition models. This article evaluates various feature selection methods, including correlation-based (CB), mutual information (MI), and ...
Alaa Altheneyan, Aseel Alhadlaq
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Learning Sparse Adversarial Dictionaries For Multi-Class Audio Classification
, 2017 Audio events are quite often overlapping in nature, and more prone to noise than visual signals. There has been increasing evidence for the superior performance of representations learned using sparse dictionaries for applications like audio denoising ...
Bhattacharya, Puranjoy, Shaj, Vaisakh
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Automatic speech recognition research at NASA-Ames Research Center [PDF]
A trainable acoustic pattern recognizer manufactured by Scope Electronics is presented. The voice command system VCS encodes speech by sampling 16 bandpass filters with center frequencies in the range from 200 to 5000 Hz.
Coler, Clayton R. +3 more
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The self organizing map of neighbour stars and its kinematical interpretation [PDF]
, 1993 The Self-Organizing Map (SOM) is a neural network algorithm that has the special property ofcreating spatially organized tepresetüatioes of various features of input signals.
Cubarsí Morera, Rafael +2 more
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