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Bibliography
The following are papers, textbooks, and
webpages that people working on the Speech Recognition using
Dynamical Systems Models project have found useful. They
are broken into categoreis according to research topics.
Happy learning!
Speech Recognition Systems
Time-Delay
Embedding
Phoneme Recognition
Phase Space
Features for Classification
Modeling Techniques
Matlab Resources
Chaos, Nonlinear/Dynamical
Signal Processing
Application of Wavelets
and Neural Networks on Speech Signal Processing
Global Vector
Field or Flow Reconstruction
Topology Analysis
Surrogate Data Method
LPC, Wiener Filter, and Kalman
Filter
Useful Downloading Sites
Speech Recognition Systems
M. Banbrook and S. McLaughlin, "Is Speech
Chaotic?: Invariant Geometric Measures for Speech Data",
IEE Colloquium on "Exploiting Chaos in Signal Processing",
Digest No 1994/193, pp8/1-8/10, June 1994. (pdf)
J. R. Deller, J. H. L. Hansen, and J. G. Proakis,
Discrete-Time Processing of Speech Signals, 2nd ed.
New York: IEEE Press, 2000.
X. Huang, A. Acero, and H.-W. Hon, Spoken
Language Processing. Upper Saddle River, New Jersey:
Prentice Hall, 2001.
F. Jelinek, Statistical Methods for Speech
Recognition. Cambridge, MA: MIT Press, 1999.
L. R. Rabiner, "Tutorial on Hidden Markov
Models and Selected Applications in Speech Recognition,"
Proceedings of the IEEE, vol. 77, no. 2, pp. 257-286, 1989.
(pdf)
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Time-Delay Embedding
H. D. I. Abarbanel, Analysis of observed
chaotic data. New York: Springer, 1996.
H. Kantz and T. Schrieber, Nonlinear Time
Series Analysis. New York, NY: Cambridge University
Press, 2000.
T. Sauer, J. A. Yorke, and M. Casdagli, "Embedology,"
Journal of Statistical Physics, vol. 65, pp. 579-616, 1991.
F. Takens, "Detecting strange attractors
in turbulence," presented at Dynamical Systems and
Turbulence, Warwick, 1980.
H. Whitney, "Differentiable Manifolds,"
The Annals of Mathematics, 2nd Series, vol. 37, pp. 645-680,
1936. (html)
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Phoneme Recognition
M. Banbrook, S. McLaughlin, and I. Mann, "Speech
characterization and synthesis by nonlinear methods,"
IEEE Transactions on Speech and Audio Processing, vol. 7,
pp. 1 -17, 1999.
K.-F. Lee and H.-W. Hon, "Speaker-independent
phone recognition using hidden Markov models," IEEE
Transactions on Acoustics, Speech and Signal Processing,
vol. 37, pp. 1641-1648, 1989.
S. C. Lee and J. R. Glass, "Real-Time
Probabilistic Segmentation for Segment-Based Speech Recognition,"
presented at ISCLP, 1998.
T. Robinson, "An application of recurrent
nets to phone probability estimation," IEEE Transactions
on Neural Networks, vol. 5, pp. 128-305, March 1994.
T. Robinson and F. Fallside, "A Recurrent
Error Propagation Network Speech recognition system,"
Computer Speech and Language, vol. 5, pp. 259-274, 1991.
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Phase Space Features for Classification
H. F. V. Boshoff and M. Grotepass, "The
Fractal Dimension of Fricative Speech Sounds," presented
at South African Symposium on Communications and Signal
Processing, 1991. papers/boshoff1991.pdf
G. Kubin, "Nonlinear Speech Processing,"
in Speech Coding and Synthesis, W. B. Kleijn and K. K. Paliwal,
Eds.: Elsevier Science, 1995.
A. Kumar and S. K. Mullick, "Nonlinear
Dynamical Analysis of Speech," Journal of the Acoustical
Society of America, vol. 100, pp. 615-629, 1996.
A. Langi and W. Kinsner, "Consonant Characterization
using Correlation Fractal Dimension for Speech Recognition,"
presented at IEEE WESCANEX Proceedings, 1995.
S. S. Narayanan and A. A. Alwan, "A Nonlinear
Dynamical Systems Analysis of Fricative Consonants,"
Journal of the Acoustical Society of America, vol. 97, pp.
2511-2524, 1995.
A. Petry, D. Augusto, and C. Barone, "Speaker
Identification using nonlinear dynamical features,"
Chaos, Solitons, and Fractals, vol. 13, pp. 221-231, 2002.
N. Tishby, "A dynamical systems approach
to speech processing," presented at ICASSP'90, 1990.
papers/tishby1990.pdf
D. M. Tumey, P. E. Morton, D. F. Ingle, C.
W. Downey, and J. H. Schnurer, "Neural Network Classification
of EEG using Chaotic Preprocessing and Phase Space Reconstruction,"
presented at 1991 IEEE Seventeenth Annual Northeast Bioengineering
Conference, 1991. papers/tumey1991.pdf
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Modeling Techniques
M. Giona, F. Lentini, and V. Cimagalli, "Functional
reconstruction and local prediction of chaotic time series,"
Physical Review A, vol. 44, pp. 3496-3502, 1991.
G. Gouesbet and C. Letellier, "Global
vector field reconstruction by using a multivariate polynomial
L2-approximation on nets," Physical Review E, vol.
49, pp. 4955-4972, 1994.
G. Gouesbet, L. L. Sceller, C. Letellier,
R. Brown, J. R. Buchler, and Z. Kollath, "Reconstructing
a dynamics from a scalar time series," presented at
Eleventh Annual Florida Workshop in Nonlinear Astronomy,
1995.
D. G. Manolakis, V. K. Ingle, and S. M. Kogon,
Statistical and Adaptive Signal Processing: McGraw Hill,
2000.
T. Serre, Z. Kollath, and J. R. Buchler, "Search
For Low - Dimensional Nonlinear Behavior in Irregular Variable
Stars - The Global Flow Reconstruction Method," Astronomy
& Astrophysics, pp. 811-833, 1996.
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Matlab Resources
C. B. Moler, and K. A. Moler, "Numerical
Computing with MATLAB," http://www.mathworks.com/moler/,
2003.
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Chaos, Nonlinear/Dynamical Signal Processing
H. D. I. Abarbanel, R. Brown, J. J. Sidorowich,
and L. S. Tsimring, "The analysis of observed chaotic
data in physical systems," Rev. Mod. Phys., v. 64,
no. 5, pp. 1331-1393, 1993. (pdf)
T. Schreiber, "Interdisciplinary application
of nonlinear time series methods," Phys. Rep. 308,
2, 1999. (pdf)
F. Grigoras, H. Teodorescu, and V. Apopei,
"Analysis of Nonlinear and Nonstationary Processes
in Speech Production," Applications of Signal Processing
to Audio and Acousics, 1997.
O. G. Barbashov, A. L. Fradkov, O.G. Maleev,
N. A. Romashov, and D. A. Yushanov, "On the improvements
of speaker-independent isolated word recognition using chaotic
model," Control of Oscillations and Chaos, 1997.
M. G. Signorini, F. Marchetti, and S. Cerutti,
"Applying Nonlinear Noise Reduction in the Analysis
of Heart Rate Variability," IEEE Engineering in Medicine
and Biology, March/April 2001, pp. 59-68.
S. R. Wilkin, and M. J. Vinson, "Nonlinear
Forecasting and Detection of Chaos,"
J. McNames, J. A. K. Suykens, and J. Vandewalle,
"Winning Entry of the K. U. Leuven Time Series Prediction
Competition," Internation Journal of Bifurcation and
Chaos, Vol. 9, No. 8, 1999. (pdf)
J. McNames, "Innovations in Local Modeling
for Time Series Prediction," Ph.D. Thesis, Stanford
University, May 1999. (pdf)
U. Parlitz, "Analysis and Synchronization
of Chaotic Systems" (ppt)
A. C. Singer, G. W. Wornell, and A. V. Oppenheim,
"Autoregressive Modeling and Estimation in the Presence
of Noise," Digital Signal Processing, Vol. 4, November
1994.
V. Babovic, and M. Keijzer, "Forecasting
of River Discharges in the Presence of Chaos and Noise,"
M. W. Slutzky, P. Cvitanovic, and D. J. Mogul,
" Deterministic chaos and Noise in Thress In Vitro
Hippocampal Models of Epilepsy," Annals of Biomedical
Engineering, Vol. 29, No. 607, 2001.
J. McNames, "A Nearest Trajectory Strategy
for Time Series Prediction," Proceedings of the International
Workshop on Advanced Black-Box Techniques for Nonlinear
Modeling, Katholieke Universiteit Leuven, Belgium, pp. 112-128,
July 1998. (pdf)
S. Singh, and P. McAtackney, "Dynamic
Time-Series Forecasting using Local Approximation,"
Proc. 10th IEEE International Conference on Tools with AI,
IEEE Press, pp. 392-399, 10-12 November 1998.
F. M. Roberts, R. J. Povinelli, and K. M.
Ropella, "Identification of ECG Arrhythias using Phase
Space Reconstruction," 5th European Conference on Principles
and Practice of Knowledge Discovery in Databases (PKDD'01),
411-423, 2001. (pdf)
J. Stehlik, "Deterministic Chaos in Runoff
Series," Journal of Hydrology and Hydromechanics, Vol
47, No. 4, pp. 271-287, 1999. (html)
An Introduction to Chaos: http://www.upscale.utoronto.ca/GeneralInterest/Harrison/Chaos/Chaos.html
How to identify low-dimensional deterministic
systems (chaos) in time series or spatial patterns: http://walrus.wr.usgs.gov/seds/
A. Yasmin, "Speech Enhancement Using
Voice Source Models,"
R. J. Povinelli. (1999). “Time Series
Data Mining: Identifying Temporal Patterns for Characterization
and Prediction of Time Series Events,” Ph.D. Dissertation,
Marquette University, Milwaukee, WI. (pdf)
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Application of Wavelets and Neural Networks
on Speech Signal Processing
Y. Romanyshyn, and V. Hudym, "Wavelet
transforms applications for speech signals processing,"
CADSM 2001. The Experience of Designing and Application
of CAD Systems in Microelectronics. Proceedings of the VI-th
International Conference , 2001 Page(s): 297 -298.
K. Nie, N. Lan, and S. Gao, "Wavelet-based
feature extraction of speech signal for cochlear implants,"
BMES/EMBS Conference, 1999. Proceedings of the First Joint
, Volume: 1 , 1999 Page(s): 654 vol.1
L. Qiu, H. Yang, and S. N. Koh, "A fundamental
frequency detector of speech signals based on short time
Fourier transform," TENCON '94. IEEE Region 10's Ninth
Annual International Conference. Theme: Frontiers of Computer
Technology. Proceedings of 1994 , 1994 Page(s): 526 -530
vol.1
H. Kabre, "Robustness of a chaotic modal
neural network applied to audio-visual speech recognition,"
Neural Networks for Signal Processing [1997] VII. Proceedings
of the 1997 IEEE Workshop , 1997 Page(s): 607 -616
H. Choi, H. Lee, S. Kim, J. Eem, and W. Park,
"Adaptive prediction of nonstationary signals using
chaotic neural networks," Neural Networks Proceedings,
1998. IEEE World Congress on Computational Intelligence.
The 1998 IEEE International Joint Conference on , Volume:
3 , 1998 Page(s): 1943 -1947 vol.3
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Global Vector Field or Flow Reconstruction
H. D. I. Abarbanel, R. Brown, J. J. Sidorowich,
and L. S. Tsimring, "The analysis of observed chaotic
data in physical systems, "Rev. Mod. Phys., Vol. 64,
No. 5, 1331-1393, 1993.
R. Brown, "Calculating Lyapunov exponents
for short and/or noisy data sets," Physical Review
E, Vol. 47, pp. 3962-3969, 1993.
J. R. Buchler, and Z. Koll, "Nonlinear
Analysis of Irregular Variables, in Nonlinear Studies of
Stellar Pulsation," Eds. M. Takeuti and D. D. Sasselov,
Astrophysics and Space Science Library Series, Vol. 257,
pp. 185-213, 2000.
G. Gouesbet, L. Le Sceller, C. Letellier,
R. Brown, J. R. Buchler, Z. Kollath, "Reconstructing
a Dynamics from a Scaler Time Series," Eleventh Annual
Florida Workshop in Nonlinear Astronomy and Physics, 1995.
G. Gouesbet and C. Letellier, "Global
vector field reconstruction by using a multivariate polynomial
L2-approximation on nets," Physical Review E, Vol.
40, No. 6, pp. 4955-4972, 1994.
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Topology Analysis
V. Robins, "Computational Topology at
Multiple Resolutions," Ph.D. Dissertation, University
of Colorado, Boulder, 2000.
M. Lefranc, P. Glorieux, F. Papoff, F. Molesti,
and E. Arimondo, "Combining Topological Analysis and
Symbolic Dynamics to Describe a Strange Attractor and its
Crises," Physical Review Letters, Vol. 73, No. 10,
pp. 1364-1367, 1994.
R. Brown, N. Rulkov, and N. B. Tufillaro,
"The effects of additive noise and drift in the dynamics
of the driving on chaotic synchronization," Physics
Letters A, Vol. 196, pp. 201-205, 1994.
N. B. Tufillaro, P. Wyckoff, R. Brown, T.
Schreiber, and T. Molteno, "Topological time series
analysis of a string expereiment and its synchronized model,"
Physical Review E, Vol. 51, No. 1, pp. 164-174, 1995.
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Surrogate Data Method
J. Theiler and D. Prichard, "Constrained-relization
Monte-Carlo method for hypothesis testing," Physica
D, Vol. 94, pp. 221-235, 1996.
D. Kugiumtzis, "Surrogate Data Test for
Nonlinearity Including Non-monotonic Transforms," Physical
Review E, Vol. 62, No. 1, pp. 25-28, 2000.
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LPC, Wiener Filter, and Kalman Filter
P. Polotti, "Speech Modeling by means
of Linear Predictive Coding (LPC)," (pdf)
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