Neuro-Fuzzy Applications in Speech Coding and Recognition

The recent growth of multimedia mobile communications based on man-machine interaction has increased the demand for advanced speech processing algorithms capable of providing good performance levels, even in adverse acoustic noise conditions (car, babble, traffic noise, etc.),with as low a computational load as possible. Robust speech classification represents, in fact, a crucial point both in speech coding and recognition, two fundamental applications in modern multimedia systems. In particular, in the field of speech coding, an accurate speech classification is fundamental in selecting the appropriate coding model and in maintaining a high perceived quality of the decoded speech. On the other hand, in the field of speech recognition, a robust signal classification is fundamental in obtaining a good word recognition rate, also in the presence of high background noise levels.

[1]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[2]  Peter Kabal,et al.  Frame level noise classification in mobile environments , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[3]  Allen Gersho,et al.  Variable bit-rate CELP coding of speech with phonetic classification : Speech coding for telecommunications , 1994 .

[4]  Marco Russo,et al.  FuGeNeSys-a fuzzy genetic neural system for fuzzy modeling , 1998, IEEE Trans. Fuzzy Syst..

[5]  Jean-Claude Junqua,et al.  Robustness in Automatic Speech Recognition: Fundamentals and Applications , 1995 .

[6]  Allen Gersho,et al.  Advances in speech and audio compression , 1994, Proc. IEEE.

[7]  Stephen A. Zahorian,et al.  Signal modeling for isolated word recognition , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[8]  Pramod K. Varshney,et al.  Discrete-Time Analysis of Integrated Voice/Data Multiplexers With and Without Speech Activity Detectors , 1983, IEEE J. Sel. Areas Commun..

[9]  R. V. Cox,et al.  Low bit-rate speech coders for multimedia communication , 1996, IEEE Commun. Mag..

[10]  Giuseppe Ruggeri,et al.  New results in fuzzy pattern classification of background noise , 2000, WCC 2000 - ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress 2000.

[11]  Sam Kwong,et al.  Genetic algorithms and their applications , 1996, IEEE Signal Process. Mag..

[12]  Aaron E. Rosenberg,et al.  An improved endpoint detector for isolated word recognition , 1981 .

[13]  Ronald W. Schafer,et al.  Digital Processing of Speech Signals , 1978 .

[14]  Lotfi A. Zadeh,et al.  Fuzzy logic, neural networks, and soft computing , 1993, CACM.

[15]  Keinosuke Fukunaga,et al.  Introduction to Statistical Pattern Recognition , 1972 .

[16]  D. H. Kil,et al.  Pattern recognition and prediction with applications to signal characterization , 1996 .

[17]  Richard J. Mammone,et al.  Speaker recognition using neural networks and conventional classifiers , 1994, IEEE Trans. Speech Audio Process..

[18]  M. Russo,et al.  FuGeNeSys: Sw and Hw implementation , 1997, Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97.

[19]  Robert M. Gray,et al.  An endpoint detector for LPC speech using residual error look-ahead for vector quantization applications , 1984, ICASSP.

[20]  Daniele Sereno,et al.  CELP coding at variable rate : Speech coding for telecommunications , 1994 .

[21]  E. Shlomot,et al.  ITU-T Recommendation G.729 Annex B: a silence compression scheme for use with G.729 optimized for V.70 digital simultaneous voice and data applications , 1997, IEEE Commun. Mag..

[22]  Luca Cellario,et al.  CELP coding at variable rate , 1994, Eur. Trans. Telecommun..

[23]  G. Cosier,et al.  Voice control of the pan-European digital mobile radio system , 1989, IEEE Global Telecommunications Conference, 1989, and Exhibition. 'Communications Technology for the 1990s and Beyond.

[24]  Joseph P. Campbell,et al.  Voiced/Unvoiced classification of speech with applications to the U.S. government LPC-10E algorithm , 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[25]  Biing-Hwang Juang,et al.  Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.

[26]  Francesco Beritelli,et al.  A robust voice activity detector for wireless communications using soft computing , 1998, IEEE J. Sel. Areas Commun..

[27]  Jean-Claude Junqua,et al.  Robustness in Automatic Speech Recognition , 1996 .

[28]  Leonardo Chiariglione.  MPEG and multimedia communications , 1997, IEEE Trans. Circuits Syst. Video Technol..

[29]  Francesco Beritelli,et al.  Robust voiced/unvoiced speech classification using fuzzy rules , 1997, 1997 IEEE Workshop on Speech Coding for Telecommunications Proceedings. Back to Basics: Attacking Fundamental Problems in Speech Coding.

[30]  F. Beritelli,et al.  Robust word boundary detection using fuzzy logic , 2000 .

[31]  Jean-Claude Junqua,et al.  A robust algorithm for word boundary detection in the presence of noise , 1994, IEEE Trans. Speech Audio Process..