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2015 | OriginalPaper | Buchkapitel

13. Stressed Speech Recognition Using Similarity Measurement on Inner Product Space

verfasst von : Bhanu Priya, S. Dandapat

Erschienen in: Advances in Communication and Computing

Verlag: Springer India

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Abstract

In this paper, similarity measurement on different inner product space approach is proposed for analysis of stressed speech. The similarity is measured between neutral speech subspace and stressed speech subspace. Cosine between neutral speech and stressed speech is taken as similarity measurement parameter. It is asssumed that, speech and stress components of stressed speech are linearly related to each other. Cosine between neutral and stressed speech multiples of stressed speech contains speech information of stressed speech. Complement cosine (1-cosine) multiples of stressed speech is taken as stress component of stressed speech. Neutral speech subspace is created by all neutral speech of the training database and stressed speech subspace contain stressed (angry, sad, lombard, happy) speech. From experiment, it is observed that, stress information of stressed speech is not present in the complement cosine (1-cosine) times of stressed speech on different inner product space. The linear relationship between speech and stress component of stressed speech exists only for some specific inner product space. All the experiments are done using nonlinear (TEO-CB-Auto-Env) feature.

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Vorheriges Kapitel Block Matching Algorithms for Motion Estimation: A Performance-Based Study
Nächstes Kapitel An Analysis of Indoor Power Line Network as a Communication Medium Using ABCD Matrices Effect of Loads on the Transfer Function of Power Line
Literatur
1.
Patil, S.A., Hansen, J.H.: Speech Under Stress: Analysis, Modeling and Recognition. Springer, Berlin (2007)
2.
Chen, Y.: Cepstral domain stress compensation for robust speech recognition. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP ’87, vol. 12, pp. 717–720 (1987)
3.
Ramamohan, S., Dandapat, S.: Sinusoidal model-based analysis and classification of stressed speech. IEEE Trans. Audio Speech Lang. Process. 14(3), 737–746 (2006)CrossRef
4.
Nwe, T., Foo, S.W., De Silva, C.: Detection of stress and emotion in speech using traditional and fft based log energy features. In: Proceedings of the 2003 Joint Conference of the Fourth International Conference on Information, Communications and Signal Processing, 2003 and Fourth Pacific Rim Conference on Multimedia, vol. 3, pp. 1619–1623 (2003)
5.
Ruzanski, E., Hansen, J., Meyerhoff, J., Saviolakis, G., Norris, W., Wollert, T.: Stress level classification of speech using euclidean distance metrics in a novel hybrid multi-dimensional feature space. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006, vol. 1, pp. I-I (2006)
6.
Loizou, P., Spanias, A.: Improved speech recognition using a subspace projection approach. IEEE Trans. Speech Audio Process. 7(3), 343–345 (1999)CrossRef
7.
Pavan Kumar, D., Bilgi, R.R., Umesh, S.: Non-negative subspace projection during conventional mfcc feature extraction for noise robust speech recognition. In: National Conference on Communications (NCC), pp. 1–5 (2013)
8.
Shukla, S., Dandapat, S., Prasanna, S.: Subspace projection based analysis of speech under stressed condition. In: World Congress on Information and Communication Technologies (WICT), pp. 831–834 (2012)
9.
Vera, E.: The subspace approach as a first stage in speech enhancement, Latin America transactions. IEEE (Revista IEEE America Latina) 9(5), 721–725 (2011)CrossRef
10.
Rabiner, L.R., Schafer, R.W.: Digital Processing of Speech Signals, vol. 19. IET, Stevenage (1979)
11.
Rabiner, L., Juang, B.-H.: Fundamentals of Speech Recognition. Prentice-Hall, Inc., Upper Saddle River (1993)
12.
Nakos, G., Joyner, D.: Linear Algebra with Applications. Brooks/Cole Publishing Company, Pacific Grove (1998)
13.
Zhou, G., Hansen, J., Kaiser, J.: Methods for stress classification: nonlinear teo and linear speech based features. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 4, pp. 2087–2090 (1999)
14.
Nwe, T.L., Foo, S., De Silva, L.: Classification of stress in speech using linear and nonlinear features. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP ’03), vol. 2, pp. II-9-12 (2003)
15.
Zhou, G., Hansen, J., Kaiser, J.: Nonlinear feature based classification of speech under stress. IEEE Trans. Speech Audio Process. 9(3), 201–216 (2001)CrossRef
Metadaten
Titel
Stressed Speech Recognition Using Similarity Measurement on Inner Product Space
verfasst von
Bhanu Priya
S. Dandapat
Copyright-Jahr
2015
Verlag
Springer India
Buch
Advances in Communication and Computing

Print ISBN: 978-81-322-2463-1

Electronic ISBN: 978-81-322-2464-8

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-81-322-2464-8_13

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