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14 results on '"Manzo-Martínez, Alain"'

8. Audio-to-Audio Alignment for Performances Tracking

Author

Manzo-Martínez, Alain, Camarena-Ibarrola, Jose Antonia, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, Series editor, Tanaka, Yuzuru, Series editor, Wahlster, Wolfgang, Series editor, Siekmann, Jörg, Series editor, Gelbukh, Alexander, editor, Espinoza, Félix Castro, editor, and Galicia-Haro, Sofía N., editor

Published
2014
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13. El paradigma del deletreo: Avances en el desarrollo de interfaces cerebro-computadora aplicadas al deletreo de palabras.

Author

Ramírez-Alonso, Graciela, Rascón-Cervantes, Kathia, and Manzo-Martínez, Alain

Abstract

Copyright of CULCyT: Cultura Científica y Tecnológica is the property of Cultura Cientifica y Tecnologia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2018
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14. A New and Efficient Alignment Technique by Cosine Distance.

Author

Manzo-Martínez, Alain and Camarena-Ibarrola, José A.

Subjects
*TIME series analysis, *MATHEMATICAL statistics, *COSINE function, *LEAST squares, *SPEECH perception
Abstract

In this paper we describe a new technique to measure the similarity or distance between time series. We have called it, Alignment Technique by Cosine Distance (ATCD). Important features about the technique are that it requires neither a-priori knowledgement of the time series nor training stages. ATCD is based on cosine distance and least squares, and requires as a parameter the dimension of two support vectors. When we consider high dimensionality on these vectors, ATCD achieves its best performance providing the smallest measure of similarity (distance) as possible. ATCD can be used on applications of medical signal processing, audio and speech recognition, among others. We proved ATCD's efficiency on an isolated-words speech recognition system by comparing ATCD against Dynamic Time Warping. [ABSTRACT FROM AUTHOR]

Published
2013

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