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Connectionist Bench (Vowel Recognition - Deterding Data) Data Set

Below are papers that cite this data set, with context shown. Papers were automatically harvested and associated with this data set, in collaboration with Rexa.info.

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M. Layton and M. J. F Gales. CAMBRIDGE UNIVERSITY ENGINEERING DEPARTMENT Maximum Margin Training of Generative Kernels. CUED. 2004.

the number of iterations required for convergence increased significantly (34 iterations were required for C = 10, whereas 1,084 were required for C = 0.1). 15 5.2 Deterding data The Deterding dataset [6] consists of the steady-state portion of 11 vowels in British English, spoken in the context of h*d. The recorded speech samples were low-pass filtered at 4.7KHz before being digitised at 10KHz


Matthew Brand. Pattern discovery via entropy minimization. MERL -- A MITSUBISHI ELECTRIC RESEARCH LABORATORY. 1998.

DA circumvents this local optimum and finds a model which generalizes even better. 9.2 Radial basis function networks (RBFNs) Vowel classification: We obtained the British English vowel recognition dataset from the CMU Neural-Bench Archive. Each example of a vowel is characterized by LPC coefficients from two time-frames. This dataset has been treated several times using perceptrons, neural networks,


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