-
1
-
-
17644442381
-
Multi-class support vector machines: A new approach
-
Hong Kong, China, Apr.
-
J. Arenas-García and F. Pérez-Cruz, “Multi-class support vector machines: A new approach,” in Proc. ICASSP, Hong Kong, China, Apr. 2003, pp. 781–784.
-
(2003)
Proc. ICASSP
, pp. 781-784
-
-
Arenas-García, J.1
Pérez-Cruz, F.2
-
3
-
-
84898983965
-
Phonetic speaker recognition with support vector machines
-
S. Thrun, L. Saul, and B. Scholköpf, Eds. Cambridge, MA: MIT Press
-
W. Campbell et al., “Phonetic speaker recognition with support vector machines,” in Adv. Neural Inf. Process. Syst. 16, S. Thrun, L. Saul, and B. Scholköpf, Eds. Cambridge, MA: MIT Press, 2004.
-
(2004)
Adv. Neural Inf. Process. Syst. 16
-
-
Campbell, W.1
-
5
-
-
84959118000
-
The Fisher corpus: A resource for the next generation of speech-to-text
-
Lisbon, Portugal, May
-
C. Cieri, D. Miller, and K. Walker, “The Fisher corpus: A resource for the next generation of speech-to-text,” in Proc. Int. Conf. Lang. Resources Eval., Lisbon, Portugal, May 2004, pp. 69–71.
-
(2004)
Proc. Int. Conf. Lang. Resources Eval.
, pp. 69-71
-
-
Cieri, C.1
Miller, D.2
Walker, K.3
-
6
-
-
0000913324
-
SVMTorch: Support vector machines for large-scale regression problems
-
R. Collobert and S. Bengio “SVMTorch: Support vector machines for large-scale regression problems,” J. Mach. Learn. Res., vol. 1, pp. 143–160, 2001.
-
(2001)
J. Mach. Learn. Res.
, vol.1
, pp. 143-160
-
-
Collobert, R.1
Bengio, S.2
-
7
-
-
0010442827
-
On the algorithmic implementation of multi-class kernel-based vector machines
-
K. Crammer and Y. Singer “On the algorithmic implementation of multi-class kernel-based vector machines,” J. Mach. Learn. Res., vol. 2, pp. 265–292, 2001.
-
(2001)
J. Mach. Learn. Res.
, vol.2
, pp. 265-292
-
-
Crammer, K.1
Singer, Y.2
-
8
-
-
33745875075
-
A MFoM learning approach to robust multiclass multi-label text categorization
-
Banff, AB, Canada, Jul.
-
S. Gao, W. Wu, C.-H. Lee, and T.-S. Chua, “A MFoM learning approach to robust multiclass multi-label text categorization,” in Proc. ICML, Banff, AB, Canada, Jul. 2004, pp. 42–49.
-
(2004)
Proc. ICML
, pp. 42-49
-
-
Gao, S.1
Wu, W.2
Lee, C.-H.3
Chua, T.-S.4
-
9
-
-
0038359548
-
A probabilistic framework for segment-based speech recognition
-
J. Glass “A probabilistic framework for segment-based speech recognition,” Comput. Speech Lang., vol. 17, no. 2–3, pp. 137–152, 2003.
-
(2003)
Comput. Speech Lang.
, vol.17
, Issue.2-3
, pp. 137-152
-
-
Glass, J.1
-
10
-
-
0141702347
-
Optimizing SVMs for complex call classification
-
Hong Kong, China, Apr.
-
P. Haffner, G. Tur, and J. Wright, “Optimizing SVMs for complex call classification,” in Proc. ICASSP, Hong Kong, China, Apr. 2003, pp. 632–635.
-
(2003)
Proc. ICASSP
, pp. 632-635
-
-
Haffner, P.1
Tur, G.2
Wright, J.3
-
11
-
-
33846200839
-
Combining feature sets with support vector machines: Application to speaker recognition
-
San Juan, Puerto Rico, Nov.
-
A. Hatch, A. Stolcke, and B. Peskin, “Combining feature sets with support vector machines: Application to speaker recognition,” in Proc. IEEE Workshop Autom. Speech Recognition Understand., San Juan, Puerto Rico, Nov. 2005, pp. 75–79.
-
(2005)
Proc. IEEE Workshop Autom. Speech Recognition Understand.
, pp. 75-79
-
-
Hatch, A.1
Stolcke, A.2
Peskin, B.3
-
12
-
-
44849114362
-
Topic identification from audio recordings using word and phone recognition lattices
-
Kyoto, Japan, Dec.
-
T. Hazen, F. Richardson, and A. Margolis, “Topic identification from audio recordings using word and phone recognition lattices,” in Proc. IEEE Workshop Autom. Speech Recognition Understand., Kyoto, Japan, Dec. 2007, pp. 659–664.
-
(2007)
Proc. IEEE Workshop Autom. Speech Recognition Understand.
, pp. 659-664
-
-
Hazen, T.1
Richardson, F.2
Margolis, A.3
-
13
-
-
51449103896
-
Discriminative feature weighting using MCE training for topic identification of spoken audio recordings
-
Las Vegas, NV, Apr.
-
T. Hazen and A. Margolis, “Discriminative feature weighting using MCE training for topic identification of spoken audio recordings,” in Proc. IEEE ICASSP, Las Vegas, NV, Apr. 2008, pp. 4965–4968.
-
(2008)
Proc. IEEE ICASSP
, pp. 4965-4968
-
-
Hazen, T.1
Margolis, A.2
-
14
-
-
84867211153
-
A hybrid SVM/MCE training approach for vector space topic identification of spoken audio recordings
-
Brisbane, Australia, Sep.
-
T. Hazen and F. Richardson, “A hybrid SVM/MCE training approach for vector space topic identification of spoken audio recordings,” in Proc. Interspeech, Brisbane, Australia, Sep. 2008, pp. 2542–2545.
-
(2008)
Proc. Interspeech
, pp. 2542-2545
-
-
Hazen, T.1
Richardson, F.2
-
15
-
-
78049376440
-
Multi-class SVM optimization using MCE training with application to topic identification
-
Dallas, TX, Mar.
-
T. Hazen, “Multi-class SVM optimization using MCE training with application to topic identification,” in Proc. IEEE ICASSP, Dallas, TX, Mar. 2010, pp. 5350–5353.
-
(2010)
Proc. IEEE ICASSP
, pp. 5350-5353
-
-
Hazen, T.1
-
16
-
-
84957069814
-
Text categorization with support vector machines: Learning with many relevant features
-
Chemnitz, Germany, Apr.
-
T. Joachims, “Text categorization with support vector machines: Learning with many relevant features,” in Proc. Eur. Conf. Mach. Learn., Chemnitz, Germany, Apr. 1998, pp. 137–142.
-
(1998)
Proc. Eur. Conf. Mach. Learn.
, pp. 137-142
-
-
Joachims, T.1
-
17
-
-
0026982122
-
Discriminative learning for minimum error classification
-
Dec.
-
B.-H. Juang and S. Katagiri “Discriminative learning for minimum error classification,” IEEE Trans. Signal Process., vol. 40, no. 12, pp. 3043–3054, Dec. 1992.
-
(1992)
IEEE Trans. Signal Process.
, vol.40
, Issue.12
, pp. 3043-3054
-
-
Juang, B.-H.1
Katagiri, S.2
-
18
-
-
0037226148
-
Discriminative training of natural language call routers
-
Jan.
-
H.-K.J. Kuo and C.-H. Lee “Discriminative training of natural language call routers,” IEEE Trans. Speech Audio Process., vol. 11, no. 1, pp. 24–35, Jan. 2003.
-
(2003)
IEEE Trans. Speech Audio Process.
, vol.11
, Issue.1
, pp. 24-35
-
-
Kuo, H.-K.J.1
Lee, C.-H.2
-
19
-
-
84957069091
-
Naive (Bayes) at forty: The independence assumption in information retrieval
-
Chemnitz, Germany, Apr.
-
D. Lewis, “Naive (Bayes) at forty: The independence assumption in information retrieval,” in Proc. Eur. Conf. Mach. Learn., Chemnitz, Germany, Apr. 1998, pp. 4–15.
-
(1998)
Proc. Eur. Conf. Mach. Learn.
, pp. 4-15
-
-
Lewis, D.1
-
20
-
-
85009110335
-
Discriminative training of naive Bayes classifiers for natural language call routing
-
Jeju Island, Korea, Oct.
-
P. Liu, H. Jiang, and I. Zitouni, “Discriminative training of naive Bayes classifiers for natural language call routing,” in Proc. Interspeech, Jeju Island, Korea, Oct. 2004, pp. 1589–1592.
-
(2004)
Proc. Interspeech
, pp. 1589-1592
-
-
Liu, P.1
Jiang, H.2
Zitouni, I.3
-
21
-
-
84964500666
-
Approaches to topic identification on the switchboard corpus
-
Adelaide, Australia, Apr.
-
J. McDonough et al., “Approaches to topic identification on the switchboard corpus,” in Proc. ICASSP, Adelaide, Australia, Apr. 1994, pp. 385–388.
-
(1994)
Proc. ICASSP
, pp. 385-388
-
-
McDonough, J.1
-
22
-
-
0003612818
-
Text categorization
-
Cambridge, MA: MIT Press, ch. 16
-
C. Manning and H. Schiitze, “Text categorization,” in Foundations of Statistical Natural Language Processing. Cambridge, MA: MIT Press, 1999, ch. 16, pp. 575–608.
-
(1999)
Foundations of Statistical Natural Language Processing
, pp. 575-608
-
-
Manning, C.1
Schiitze, H.2
-
23
-
-
0003243224
-
Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
-
Cambridge, MA: MIT Press
-
J. Platt, “Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods,” in Advances in Large Margin Classifiers. Cambridge, MA: MIT Press, 1999, pp. 61–74.
-
(1999)
Advances in Large Margin Classifiers
, pp. 61-74
-
-
Platt, J.1
-
24
-
-
0141534963
-
RPROP—A fast adaptive learning algorithm
-
Antalya, Turkey
-
M. Riedmiller and H. Braun, “RPROP—A fast adaptive learning algorithm,” in Proc. Int. Symp. Comput. Inf., Antalya, Turkey, 1992, pp. 279–285.
-
(1992)
Proc. Int. Symp. Comput. Inf.
, pp. 279-285
-
-
Riedmiller, M.1
Braun, H.2
-
25
-
-
85135196934
-
A maximum likelihood model for topic classification of broadcast news
-
Rhodes, Greece, Sep.
-
R. Schwartz, T. Imai, L. Nguyen, and J. Makhoul, “A maximum likelihood model for topic classification of broadcast news,” in Proc. Eurospeech, Rhodes, Greece, Sep. 1997, pp. 1455–1458.
-
(1997)
Proc. Eurospeech
, pp. 1455-1458
-
-
Schwartz, R.1
Imai, T.2
Nguyen, L.3
Makhoul, J.4
-
26
-
-
0002442796
-
Machine learning in automated text categorization
-
F. Sebastiani “Machine learning in automated text categorization,” ACM Comput. Surv., vol. 34, no. 1, pp. 1–47, 2002.
-
(2002)
ACM Comput. Surv.
, vol.34
, Issue.1
, pp. 1-47
-
-
Sebastiani, F.1
-
28
-
-
70450177185
-
Techniques for rapid and robust topic identification of conversational telephone speech
-
Brighton, U.K., Sept.
-
J. Wintrode and S. Kulp, “Techniques for rapid and robust topic identification of conversational telephone speech,” in Proc. Interspeech, Brighton, U.K., Sept. 2009, pp. 1471–1474.
-
(2009)
Proc. Interspeech
, pp. 1471-1474
-
-
Wintrode, J.1
Kulp, S.2
-
29
-
-
0003141935
-
A comparative study on feature selection in text categorization
-
Nashville, TN, Jul.
-
Y. Yang and J. Pedersen, “A comparative study on feature selection in text categorization,” in Proc. Int. Conf. Mach. Learn. (ICML), Nashville, TN, Jul. 1997, pp. 412–420.
-
(1997)
Proc. Int. Conf. Mach. Learn. (ICML)
, pp. 412-420
-
-
Yang, Y.1
Pedersen, J.2
-
30
-
-
64849099270
-
Constrained minimization and discriminative training for natural language call routing
-
Jan.
-
I. Zitouni “Constrained minimization and discriminative training for natural language call routing,” IEEE Trans. Speech Audio Process., vol. 16, no. 1, pp. 208–215, Jan. 2008.
-
(2008)
IEEE Trans. Speech Audio Process.
, vol.16
, Issue.1
, pp. 208-215
-
-
Zitouni, I.1
|