A Retrospective Assessment of Fuzzy Logic Applications in Voice Communications and Speech Analytics

Authors

  • Horia-Nicolai L. Teodorescu

Keywords:

fuzzy logic, fuzzy system, speech, communication, VAD, speech segmen- tation, speech coding, speech analytics

Abstract

Voice and speech communication is a major topic covering simultaneously ’communication’, ’control’ (because it often involves control in the coding algorithms), and ’computing’ - from speech analysis and recognition, to speech analytics and to speech coding over communication channels. While fuzzy logic was specifically con- ceived to deal with language and reasoning, it has yet a limited use in the referred field. We discuss some of the main current applications from the perspective of half a century since fuzzy logic inception.

Author Biography

Horia-Nicolai L. Teodorescu

Associate Editor in Chief of IJCCC

Rector of Agora University

References

Amir N., Kerret O., Karlinski D.(2001); Classifying emotions in speech: a comparison of methods, 7th EUROSPEECH Proc., Aalborg, 127-130.

Austermann, A., Esau, N., Kleinjohann, L., Kleinjohann, B. (2005); Fuzzy emotion recognition in natural speech dialogue, Robot and Human Interactive Communication, ROMAN 2005, IEEE Int. Workshop on, 13-15 Aug. 2005, 317-322.

Ben Jebara S., Ben Amor T. (2004); On improving voice activity detection by fuzzy logic rules: case of coherence based features, Proc. Signal Processing Conference, 2004, 12th European, 725 - 728.

Ben Jebara S. (2002); Coherence-based voice activity detector, IEE Electronic Lett., 38(22):1393-1397. http://dx.doi.org/10.1049/el:20020914

Ben Jebara S. (2008); Voice Activity Detection Using Periodioc/Aperiodic Coherence Features, Signal Processing Conference, 2008, 16th European, Lausanne, Switzerland, 1-5.

Beritelli F., Casale S., Cavallaro A. (1999); A multi-channel speech/silence detector based on time delay estimation and fuzzy classification, Proc. IEEE Int. Conf. ASSP, Phoenix, AZ, 15-19 Mar 1999, Vol. 1: 93-96.

Beritelli F., Casale S., Cavallaro A. (1998); A robust voice activity detector for wireless communications using soft computing. IEEE J. Selected Areas Comm, 16(9): 1818-1829. 870 H.-N.L. Teodorescu

Beritelli F., Casale S., G. Ruggeri, S. Serrano (2002); Performance evaluation and comparison of G.729-AMR-fuzzy voice activity detectors, IEEE Signal Process Lett, 9(3): 85-88. http://dx.doi.org/10.1109/97.995824

Beritelli F., Casale S., Cavallaro A. (1998); Adaptive voice activity detection for wireless communications based on hybrid fuzzy learning, Global Telecommunications Conference, 1998. GLOBECOM 1998. The Bridge to Global Integration. IEEE, 3: 1729 - 1734.

Christer Carlsson (2013); On the Relevance of Fuzzy Sets in Analytics. In R. Seising, E. Trillas, C. Moraga, S. Termini (Eds.), On Fuzziness, Studies in Fuzziness and Soft Computing, 298: 83-89. http://dx.doi.org/10.1007/978-3-642-35641-4_13

Carvalho, J.P., Batista F., Coheur L. (2012); A Critical Survey on the use of Fuzzy Sets in Speech and Natural Language Process, Fuzzy Systems (FUZZ-IEEE), 2012 IEEE Interna- tional Conference on, 1-8.

Cavallaro A., Beritelli F., Casale S (1998), A Fuzzy Logic-Based Speech Detection Algorithm For Communications in Noisy Environments, Proc. 1998 IEEE Int. Conf. Acoustics, Speech and Signal Process, 1: 565-568. http://dx.doi.org/10.1109/icassp.1998.674493

Chen Y.-L., Weng C.-H. (2009); Mining fuzzy association rules from questionnaire data, Knowledge-Based Systems, 22: 46-56. http://dx.doi.org/10.1016/j.knosys.2008.06.003

Cheng RG, Chang C.J. (1996); Design of a fuzzy traffic controller for ATM networks, IEEE- ACM Trans. Networking, 4(3):460-469. http://dx.doi.org/10.1109/90.502244

Cowie, R., Douglas-Cowie, E., Tsapatsoulis, N.,Votsis, G., Kollias, S., Fellenz, W., Taylor, J.G. (2001); Emotion recognition in human-computer interaction, IEEE Signal Process Magazine, 18(1): 32-80. http://dx.doi.org/10.1109/79.911197

Dhavarudha E, Charoenlarpnopparut C, Runggeratigul S (2015); Traffic Control Based on Contention Resolution in Optical Burst, International Journal of Computers Communica- tions & Control, 10(1); 49-61. http://dx.doi.org/10.15837/ijccc.2015.1.461

El Ayadi M., Kamel M.S., Karray F. (2011); Survey on speech emotion recognition: Features, classification schemes, and databases, Pattern Recognition, 44(3): 572-587. http://dx.doi.org/10.1016/j.patcog.2010.09.020

Fenn J. (2006); Survey Shows Adoption and Value of Emerging Technologies. Gartner Research, 23 March 2006, Number G00138453.

Feraru, S.M., Teodorescu, H.N., Zbancioc, M.D. (2010); SRoL - Web-based Resources for Languages and Language Technology e-Learning, International Journal of Computers Com- munications & Control, 5(3): 301-313.

Gharavian D., Sheikhan M., Nazerieh A., Garoucy S. (2012); Speech emotion recognition using FCBF feature selection method and GA-optimized fuzzy ARTMAP neural network. Neural Computing and Applications, 21(8): 2115-2126. http://dx.doi.org/10.1007/s00521-011-0643-1

Grimm, M., Kroschel, K., Narayanan, S. (2007); Support Vector Regression for Automatic Recognition of Spontaneous Emotions in Speech, Proc. ICASSP 2007, Honolulu, HI, 4: 1085-1088.

Grimm, M., Kroschel, K., Mower, E., Narayanan, S. (2007); Primitives-based evaluation and estimation of emotions in speech, Speech Commun, 49(10-11): 787-800. http://dx.doi.org/10.1016/j.specom.2007.01.010

Grimm M., Kroschel K. (2007); Rule-Based Emotion Classification Using Acoustic Features, Speech Communication; 49(10): 787-800.

Hsieh C.T., Su M.C., Lai E., Hsu C.H. (1999); A Segmentation Method for Continuous Speech Utilizing Hybrid Neuro-Fuzzy Network. J. Information Sci. & Engineering, 15, 615- 628.

Juang C.-F., Cheng C.-N., Chen T.M. (2009); Speech detection in noisy environments by wavelet energy-based recurrent neural fuzzy network. Expert Systems with Applications, 36(1):321-332. http://dx.doi.org/10.1016/j.eswa.2007.10.028

Kamaruddin, N., Nanyang, Wahab, A (2010);, Driver behavior analysis through speech emotion understanding, IEEE Intell Vehicles Symp 2010, San Diego, CA, 238-243. DOI: 10.1109/IVS.2010.5548124 http://dx.doi.org/10.1109/IVS.2010.5548124

Kamaruddin N.,Wahab A., Quek C. (2012); Cultural dependency analysis for understanding speech emotion. Expert Systems with Applications, 39(5): 5115-5133. http://dx.doi.org/10.1016/j.eswa.2011.11.028

Kamaruddin N.,Wahab A. (2009); Features extraction for speech emotion. J. Computational Methods in Science and Engineering, 9(1- Suppl.): 11-12.

Kasabov, N., Iliev, G. (2000); Hybrid system for robust recognition of noisy speech based on evolving fuzzy neural networks and adaptive filtering, Proc. Int. Conf. IJCNN 2000, 24-27 Jul 2000, Como, Italy, 5: 91-96. DOI:10.1109/IJCNN.2000.861440 http://dx.doi.org/10.1109/IJCNN.2000.861440

Kaufmann M.A. (2008); Inductive Fuzzy Classification in Marketing Analytics (Fuzzy Man- agement Methods), Springer [Kindle Edition].

Kaufmann M.A., E. Portmann, M. Fathi (2013); A Concept of Semantics Extraction from Web Data by Induction of Fuzzy Ontologies, 2013 IEEE Int. Conf. Electro-Information Tech EIT, 1-6.

Kazemzadeh A., Lee S, and Narayanan S (2013); Fuzzy Logic Models for the Meaning of Emotion Words, IEEE Computational intelligence magazine, 8(2): 34-49. http://dx.doi.org/10.1109/MCI.2013.2247824

Lee C.M., Narayanan S.S. (2005); Toward detecting emotions in spoken dialogs, IEEE Trans Speech and Audio Process, 13(2): 293-303. http://dx.doi.org/10.1109/TSA.2004.838534

Lee CM, Narayanan S. (2003); Emotion recognition using a data-driven fuzzy inference system, Proc. EUROSPEECH, Geneva, 157-160.

Lin, C.T.,Wu, R.C.,Wu, G.D.(2002); Noisy Speech Segmentation-Enhancement with Multiband Analysis and Neural Fuzzy Networks, Int J Pattern Recognition and AI, 16(7): 927-955.

Ndousse, T.D. (1994); Fuzzy neural control of voice cells in ATM networks, IEEE J. on Selected Areas in Communications, 12(9): 1488 - 1494. http://dx.doi.org/10.1109/49.339916

Ndousse, T.D. (1998); Fuzzy expert systems in a TM networks, in Fusion of Neural Net- works, Fuzzy Systems and Genetic Algorithms: Industrial Applications, Lakhmi C. Jain, N.M. Martin (Eds.), CRC Press, Boca Raton, USA, 229-284.

Pavaloi, I., Rotaru F.(2011); A Study on Duration for Different Pronunciations in Emotional States, Proc. 3rd Int. Conf. EHB, Iasi, Romania.

T. Polzehl and F. Metze (2008); Using prosodic features to prioritize voice messages, Proc. Searching Spontaneous Conversational Speech Workshop SIGIR 2008, Singapore, July 2008, ACM.

Qin Y., Zhang X., Ying H. (2010); A HMM-based fuzzy affective model for emotional speech synthesis, 2nd Int. Conf. ICSPS, 3: 525-528. DOI: 10.1109/ICSPS.2010.5555658. http://dx.doi.org/10.1109/ICSPS.2010.5555658

Ramirez J. et al. (2004); Efficient voice activity detection algorithms using long-term speech information, Speech Commun, 42: 271-287. http://dx.doi.org/10.1016/j.specom.2003.10.002

Rodriguez W., Teodorescu HN, Grigoras F., Kandel, A., Bunke, H.(2002); A fuzzy information space approach to speech signal non-linear analysis, Int. J. Intelligent Systems, 15(4): 343-363. http://dx.doi.org/10.1002/(SICI)1098-111X(200004)15:43.0.CO;2-M

Sheikhan M, Garoucy S.(2010); Reducing the Codebook Search Time in G.728 Speech Coder Using Fuzzy ARTMAP Neural Networks, World Applied Sciences Journal, 8(10): 1260-1266.

Spanias A.S. (1994); Speech Coding: A Tutorial Review. Proc. of the IEEE, 82(10):1541 - 1582. http://dx.doi.org/10.1109/5.326413

Temko A., Macho D., Nadeu C.(2008); Fuzzy integral based information fusion for classification of highly confusable non-speech sounds. Pattern Recognition, 41(5):1814-1823. http://dx.doi.org/10.1016/j.patcog.2007.10.026

Tian Y., Wu J., Wang Z., Lu D. (2003); Fuzzy clustering and Bayesian information criterion based threshold estimation for robust voice activity detection. 2003 IEEE Int. Conf. ASSP - ICASSP'03, 1: 444-447.

Toledano D.T., RodrĂguez Crespo M. A. (1998); Escalada Sardina J. G. (1998); Trying to Mimic Human Segmentation of Speech using HMM and Fuzzy Logic Post-correction Rules, 3rd ESCA/COCOSDA Workshop (ETRW), Nov. 26-29, SSW3-1998, 207-212.

Zare, H., Adibnia,F., Derhami, V. (2013); A Rate based Congestion Control Mechanism Using Fuzzy Controller in MANETs, International Journal of Computers Communications & Control, 8(3): 486-491. http://dx.doi.org/10.15837/ijccc.2013.3.244

Yang M., Kiang M., Ku Y., Chiu C., Li Y. (2011); Social Media Analytics for Radical Opinion Mining in Hate Group Web Forums, J. Homeland Security and Emergency Management, 8(1): 1547-7355. http://dx.doi.org/10.2202/1547-7355.1801

Zadeh, L.A. (1975); Concept of a Linguistic Variable and Its Application to Approximate Reasoning. 1. Information Sciences, 8(3): 199-249. http://dx.doi.org/10.1016/0020-0255(75)90036-5

Zbancioc M., Feraru M. (2012); The Analysis of the FCM and WKNN Algorithms Performance for the Emotional Corpus SROL, Advances Electrical Comput Engng, 12(3): 33-38, DOI: 10.4316/AECE.2012.03005. http://dx.doi.org/10.4316/aece.2012.03005

Zhao H., Wang G, Xu C., Yu F. (2011); Voice activity detection method based on multivalued coarse-graining Lempel-Ziv complexity. Comput. Sci. Inf. Syst., 8(3): 869-888. http://dx.doi.org/10.2298/CSIS100906032Z

http://saphanatutorial.com/sap-hana-fuzzy-search/

Published

2015-10-03

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.