Speaker Diarization: A Review of Recent Research

IEEE Transactions on Audio, Speech and Language Processing

Volumn 20, Issue 2, 2012, Pages 356-370

  Miro, Xavier Anguera ^a   Bozonnet, Simon ^b   Evans, Nicholas ^b   Fredouille, Corinne ^c   Friedland, Gerald ^d   Vinyals, Oriol ^d  

^a TELEFONICA RESEARCH   (Spain)

^b EURECOM   (France)

^c UNIVERSITY OF AVIGNON   (France)

^d INTERNATIONAL COMPUTER SCIENCE INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85008530405     PISSN: 15587916     EISSN: 15587924     Source Type: Journal    
DOI: 10.1109/TASL.2011.2125954     Document Type: Article

References (130)

1. “The NIST Rich Transcription 2009 (RT′09) Evaluation,” NIST, 2009 [Online]. Available: http://www.itl.nist.gov/iad/mig/tests/rt/2009/docs/rt09-meeting-eval-plan-v2.pdf.
2. S. Tranter and D. Reynolds, “An overview of automatic speaker diarization systems,” IEEE Trans. Audio, Speech, Lang. Process., vol. 14, no. 5, pp. 1557–1565, Sep. 2006.
3. N. Mirghafori and C. Wooters, “Nuts and flakes: A study of data characteristics in speaker diarization,” in Proc. ICASSP, 2006.
4. X. Anguera, “Robust speaker diarization for meetings,” Ph. D. dissertation, Univ. Politecnica de Catalunya, Barcelona, Spain, 2006.
5. M. Kotti, E. Benetos, and C. Kotropoulos, “Computationally efficient and robust BIC-based speaker segmentation,” IEEE Trans. Audio, Speech, Lang. Process., vol. 16, no. 5, pp. 920–933, Jul. 2008.
6. X. Zhu, C. Barras, L. Lamel, and J. -L. Gauvain, “Multi-stage speaker diarization for conference and lecture meetings,” in Proc. Multimodal Technol. Perception ofHumans: Int. Eval. Workshops CLEAR 2007 and RT 2007, Baltimore, MD, May 8--11, 2007, Revised Selected Papers, Berlin, Heidelberg: Springer-Verlag, 2008, pp. 533–542.
7. S. Jothilakshmi, V. Ramalingam, and S. Palanivel, “Speaker diarization using autoassociative neural networks,” Eng. Applicat. Artif. Intell., vol. 22, no. 4-5, pp. 667–675, 2009.
8. X. Anguera, C. Wooters, and J. Hernando, “Robust speaker diarization for meetings: ICSI RT06s evaluation system,” in Proc. ICSLP, Pittsburgh, PA, Sep. 2006.
9. C. Wooters and M. Huijbregts, “The ICSI RT07s speaker diarization system,” in Multimodal Technologies for Perception ofHumans: International Evaluation Workshops CLEAR 2007 and RT 2007, Baltimore, MD, USA, May 8--11, 2007, Revised Selected Papers, Berlin, Heidelberg: Springer-Verlag, 2008, pp. 509–519.
10. J. Rougui, M. Rziza, D. Aboutajdine, M. Gelgon, and J. Martinez, “Fast incremental clustering of Gaussian mixture speaker models for scaling up retrieval in on-line broadcast,” in Proc. ICASSP, May 2006, vol. 5, pp. 521–524.
11. W. Tsai, S. Cheng, and H. Wang, in Proc. ICSLP, 2004.
12. T. H. Nguyen, E. S. Chng, and H. Li, “T-test distance and clustering criterion for speaker diarization,” in Proc. Interspeech, Brisbane, Australia, 2008.
13. T. Nguyen, et al., “The IIR-NTU speaker diarization systems for RT 2009,” in Proc. RT′09, NIST Rich Transcription Workshop, Melbourne, FL, 2009.
14. S. Meignier, J. -F. Bonastre, and S. Igounet, “E-HMM approach for learning and adapting sound models for speaker indexing,” in Proc. Odyssey Speaker and Lang. Recognition Workshop, Chania, Creete, Jun. 2001, pp. 175–180.
15. C. Fredouille and N. Evans, “The LIA RT′07 speaker diarization system,” in Proc. Multimodal Technol. for Perception of Humans: Int. Eval. Workshops CLEAR 2007 and RT 2007, Baltimore, MD, USA, May 8--11, 2007, Revised Selected Papers, Berlin, Heidelberg: Springer-Verlag, 2008, pp. 520–532.
16. C. Fredouille, S. Bozonnet, and N. W. D. Evans, “TheLIA-EURECOM RT′09 speaker diarization system,” in Proc. RT′09, NIST Rich Transcription Workshop, Melbourne, FL, 2009.
17. S. Bozonnet, N. W. D. Evans, and C. Fredouille, “TheLIA-EURECOM RT′09 speaker diarization system: Enhancements in speaker modelling and cluster purification,” in Proc. ICASSP, Dallas, TX, Mar. 14-19, 2010, pp. 4958–4961.
18. D. Vijayasenan, F. Valente, and H. Bourlard, “Agglomerative information bottleneck for speaker diarization of meetings data,” in Proc. ASRU, Dec. 2007, pp. 250–255.
19. D. Vijayasenan, F. Valente, and H. Bourlard, “Aninformationtheoretic approach to speaker diarization of meeting data,” IEEE Trans. Audio, Speech, Lang. Process., vol. 17, no. 7, pp. 1382–1393, Sep. 2009.
20. S. McEachern, “Estimating normal means with a conjugate style dirichlet process prior,” in Proc. Commun. Statist.: Simul. Comput., 1994, vol. 23, pp. 727–741.
21. G. E. Hinton and D. van Camp, “Keeping the neural networks simpleby minimizing the description length of the weights,” in Proc. 6th Annu. Conf. Comput. Learn. Theory, New York, 1993, COLT ′93, pp. 5–13.
22. M. J. Wainwright and M. I. Jordan, “Variational inference in graphical models: The view from the marginal polytope,” in Proc. 41st Annu. Allerton Conf. Commun., Control, Comput., Urbana-Champaign, IL, 2003.
23. F. Valente, “Variational Bayesian methods for audio indexing,” Ph. D. dissertation, Eurecom Inst., Sophia-Antipolis, France, 2005.
24. D. Reynolds, P. Kenny, and F. Castaldo, “A study of new approaches to speaker diarization,” in Proc. Interspeech, 2009.
25. P. Kenny, “Bayesian Analysis of Speaker Diarization with Eigenvoice Priors,” Technical Report. Montreal, QC, Canada: CRIM, 2008.
26. X. Anguera and J. -F. Bonastre, “A novel speaker binary key derived from anchor models,” in Proc. Interspeech, 2010.
27. X. Anguera and J. -F. Bonastre, “Fast speaker diarization based on binary keys,” in Proc. ICASSP, 2011.
28. Y. Huang, O. Vinyals, G. Friedland, C. Muller, N. Mirghafori, and C. Wooters, “A fast-match approach for robust, faster than real-time speaker diarization,” in Proc. IEEE Workshop Autom. Speech Recognition Understanding, Kyoto, Japan, Dec. 2007, pp. 693–698.
29. G. Friedland, J. Ching, and A. Janin, “Parallelizing speaker-attributed speech recognition for meeting browsing,” in Proc. IEEE Int. Symp. Multimedia, Taichung, Taiwan, Dec. 2010, pp. 121–128.
30. X. Anguera, C. Wooters, and J. Hernando, “Friends and enemies: A novel initialization for speaker diarization,” in Proc. ICSLP, Pittsburgh, PA, Sep. 2006.
31. J. Ajmera, “A robust speaker clustering algorithm,” in Proc. ASRU, 2003, pp. 411--416.
32. X. Anguera, C. Wooters, and J. Hernando, “Purity algorithms for speaker diarization of meetings data,” in Proc. ICASSP, Toulouse, France, May 2006, pp. 1025--1028.
33. S. S. Chen and P. S. Gopalakrishnan, “Speaker, environment and channel change detection and clustering via the bayesian information criterion,” in Proc. DARPA Broadcast News Transcription and Understanding Workshop, Lansdowne, VA, Feb. 1998, pp. 127--132.
34. H. Gish and M. Schmidt, “Text independent speaker identification,” IEEE Signal Process. Mag., vol. 11, no. 4, pp. 18--32, Oct. 1994.
35. A. Janin, J. Ang, S. Bhagat, R. Dhillon, J. Edwards, J. Macias-Guarasa, N. Morgan, B. Peskin, E. Shriberg, A. Stolcke, C. Wooters, and B. Wrede, “The ICSI meeting project: Resources and research,” in Proc. ICASSP Meeting Recognition Workshop, 2004.
36. I. McCowan, J. Carletta, W. Kraaij, S. Ashby, S. Bourban, M. Flynn, M. Guillemot, T. Hain, J. Kadlec, V. Karaiskos, M. Kronenthal, G. Lathoud, M. Lincoln, A. Lisowska, W. Post, D. Reidsma, and P. Wellner, “The AMI meeting corpus,” in Proc. Meas. Behavior, 2005.
37. D. Mostefa, N. Moreau, K. Choukri, G. Potamianos, S. M. Chu, A. Tyagi, J. R. Casas, J. Turmo, L. Cristoforetti, F. Tobia, A. Pnev-matikakis, V. Mylonakis, F. Talantzis, S. Burger, R. Stiefelhagen, K. Bernardin, and C. Rochet, “The CHIL audiovisual corpus for lecture and meeting analysis inside smart rooms,” Lang. Resources Eval., vol. 41, Dec. 2007.
38. C. Fredouille, D. Moraru, S. Meignier, L. Besacier, and J. -F. Bonastre, “The NIST 2004 spring rich transcription evaluation: Two-axis merging strategy in the context of multiple distant microphone based meeting speaker segmentation,” in Proc. NIST 2004 Spring Rich Transcript. Eval. Workshop, Montreal, QC, Canada, 2004.
39. Q. Jin, K. Laskowski, T. Schultz, and A. Waibel, “Speaker segmentation and clustering in meetings,” in Proc. ICSLP, Jeju, Korea, Sep. 2004.
40. D. Istrate, C. Fredouille, S. Meignier, L. Besacier, and J. -F. Bonastre, “NIST RT05S evaluation: Pre-processing techniques and speaker diarization on multiple microphone meetings,” in Proc. NIST 2005 Spring Rich Transcript. Eval. Workshop, Edinburgh, U. K., Jul. 2005.
41. X. Anguera, C. Wooters, B. Peskin, and M. Aguilo, “Robust speaker segmentation for meetings: The ICSI-SRI spring 2005 diarization system,” in Proc. NIST MLMI Meeting Recognition Workshop, Edinburgh, U. K., 2005.
42. X. Anguera, C. Wooters, and J. Hernando, “Acoustic beamforming for speaker diarization of meetings,” IEEE Trans. Audio, Speech, Lang. Process., vol. 15, no. 7, pp. 2011--2023, Sep. 2007.
43. X. Anguera, BeamformIt (The Fast and Robust Acoustic Beamformer) [Online]. Available: http://www.xavieranguera.com/beamformit/.
44. N. Wiener, Extrapolation, Interpolation, and Smoothing of Stationary Time Series. New York: Wiley, 1949.
45. A. Adami, L. Burget, S. Dupont, H. Garudadri, F. Grezl, H. Her-mansky, P. Jain, S. Kajarekar, N. Morgan, and S. Sivadas, “Qual-comm-ICSI-OGI features for ASR,” in Proc. ICSLP, 2002, vol. 1, pp. 4--7.
46. M. L. Seltzer, B. Raj, and R. M. Stern, “Likelihood maximizing beam-forming for robust hands-free speech recognition,” IEEE Trans. Speech Audio Process., vol. 12, no. 5, pp. 489–498, Sep. 2004.
47. L. J. Griffiths and C. W. Jim, “An alternative approach to linearly constrained adaptive beamforming,” IEEE Trans. Antennas Propagat., vol. AP-30, no. 1, pp. 27--34, Jan. 1982.
48. M. Woelfel and J. McDonough, Distant Speech Recognition. New York: Wiley, 2009.
49. C. Wooters, J. Fung, B. Peskin, and X. Anguera, “Towards robust speaker segmentation: The ICSI-SRI fall 2004 diarization system,” in Proc. Fall 2004 Rich Transcript. Workshop (RT04), Palisades, NY, Nov. 2004.
50. J. Ramirez, J. M. Girriz, and J. C. Segura, M. Grimm and K. Kroschel, Eds., “Voice activity detection. Fundamentals and speech recognition systemrobustness,” in Proc. Robust Speech Recognit. Understand., Vienna, Austria, Jun. 2007, p. 460.
51. C. Fredouille and G. Senay, “Technical improvements of the E-HMM based speaker diarization system for meeting records,” in Proc. MLMI Third Int. Workshop, Bethesda, MD, USA, Revised Selected Paper, Berlin, Heidelberg: Springer-Verlag, 2006, pp. 359--370.
52. D. A. V. Leeuwen and M. Konecn$yA, “Progress in the AMIDA speaker diarization system for meeting data,” in Proc. Multimodal Technol. for Percept. of Humans: Int. Eval Workshops CLEAR 2007 and RT 2007, Baltimore, MD, May 8-11, 2007, Revised Selected Papers, Berlin, Heidelberg: Springer-Verlag, 2008, pp. 475--483.
53. A. Rentzeperis, A. Stergious, C. Boukis, A. Pnevmatikakis, and L. Polymenakos, “The 2006 Athens information technology speech activity detection and speaker diarization systems,” in Proc. Mach. Learn. Multimodal Interaction: 3rd Int. Workshop, MLMI 2006, Bethesda, MD, Revised Selected Paper, Berlin, Heidelberg: Springer-Verlag, 2006, pp. 385--395.
54. A. Temko, D. Macho, and C. Nadeu, “Enhanced SVM training for robust speech activity detection,” in Proc. ICASSP, Honolulu, HI, 2007, pp. 1025--1028.
55. X. Anguera, C. Wooters, M. Anguilo, and C. Nadeu, “Hybrid speech/non-speech detector applied to speaker diarization of meetings,” in Proc. Speaker Odyssey Workshop, Puerto Rico, Jun. 2006.
56. H. Sun, T. L. Nwe, B. Ma, and H. Li, “Speaker diarization for meeting room audio,” in Proc. Interspeech′09, Sep. 2009.
57. T. L. Nwe, H. Sun, H. Li, and S. Rahardja, “Speaker diarization in meeting audio,” in Proc. ICASSP, Taipei, Taiwan, 2009, pp. 4073--4076.
58. E. El-Khoury, C. Senac, and J. Pinquier, “Improved speaker diariza-tion system for meetings,” in Proc. ICASSP, Taipei, Taiwan, 2009, pp. 4097--4100.
59. L. Lu, H. -J. Zhang, and H. Jiang, “Content analysis for audio classification and segmentation,” IEEE Trans. Speech Audio Process., vol. 10, no. 7, pp. 504--516, Oct. 2002.
60. R. Li, Q. Jin, and T. Schultz, “Improving speaker segmentation via speaker identification and text segmentation,” in Proc. Interspeech, Sep. 2009, pp. 3073--3076.
61. M. Ben, M. Betser, F. Bimbot, and G. Gravier, “Speaker diarization using bottom-up clustering based on a parameter-derived distance between adapted gmms,” in Proc. ICSLP, Jeju Island, Korea, 2004.
62. D. Van Leeuwen and M. Huijbregts, “The AMI speaker diarization system for NIST RT06s meeting data,” in Machine Learning for Multimodal Interaction. Berlin, Germany: Springer-Verlag, 2007, vol. 4299, Lecture Notes in Computer Science, pp. 371--384.
63. A. Vandecatseye, J. -P. Martens, J. Neto, H. Meinedo, C. Garcia-Mateo, J. Dieguez, F. Mihelic, J. Zibert, J. Nouza, P. David, M. Pleva, A. Cizmar, H. Papageorgiou, and C. Alexandris, “The cost278 pan-European broadcast news database,” in Proc. LREC, Lisbon, Portugal, 5, 2004, vol. 4, pp. 873--876.
64. K. Mori and S. Nakagawa, “Speaker change detection and speaker clustering using VQ distortion for broadcast news speech recognition,” in Proc. ICASSP, 2001, pp. 413--416.
65. J. Ajmera and I. McCowan, “Robust speaker change detection,” IEEE Signal Process. Lett., vol. 11, pp. 649--651, 2004.
66. L. Lu and H. -J. Zhang, “Real-time unsupervised speaker change detection,” in 16th Int. Conf. Pattern Recognit., 2002, vol. 2, pp. 358--361.
67. X. Anguera and J. Hernando, “Evolutive speaker segmentation using a repository system,” in Proc. Interspeech, 2004.
68. X. Anguera, C. Wooters, and J. Hernando, “Speaker diarization for multi-party meetings using acoustic fusion,” in Proc. ASRU, Nov. 2005, pp. 426--431.
69. A. Malegaonkar, A. Ariyaeeinia, P. Sivakumaran, and J. Fortuna, “Unsupervised speaker change detection using probabilistic pattern matching,” IEEE Signal Process. Lett., vol. 13, no. 8, pp. 509--512, Aug. 2006.
70. M. -H. Siu, G. Yu, and H. Gish, “Segregation of speakers for speech recognition and speaker identification,” in Proc. ICASSP′91, 1991, pp. 873--876.
71. P. Delacourt and C. Wellekens, “DISTBIC: A speaker-based segmentation for audio data indexing,” Speech Commun., pp. 111--126, 2000.
72. S. S. Han and K. J. Narayanan, “Agglomerative hierarchical speaker clustering using incremental Gaussian mixture cluster modeling,” in Proc. Interspeech′08, Brisbane, Australia, 2008, pp. 20--23.
73. R. Gangadharaiah, B. Narayanaswamy, and N. Balakrishnan, “A novel method for two speaker segmentation,” in Proc. ICSLP, Jeju, Korea, Sep. 2004.
74. D. Liu and F. Kubala, “Fast speaker change detection for broadcast news transcription and indexing,” in Proc. Eurospeech′99, Sep. 1999, pp. 1031–1034.
75. M. A. Siegler, U. Jain, B. Raj, and R. M. Stern, “Automatic segmentation, classification and clustering of broadcast news audio,” in Proc. DARPA Speech Recognit. Workshop, 1997, pp. 97–99.
76. P. Zochova and V. Radova, “Modified DISTBIC algorithm for speaker change detection,” in Proc. 9th Eur. Conf. Speech Commun. Technol., Bonn, Germany, 2005, pp. 3073–3076.
77. X. Zhu, C. Barras, L. Lamel, and J. -L. Gauvain, “Speaker diarization: From broadcast news to lectures,” in Proc. MLMI, 2006, pp. 396–406.
78. K. Han and S. Narayanan, “Novel inter-cluster distance measure combining GLR and ICR for improved agglomerative hierarchical speaker clustering,” in Proc. ICASSP, Apr. 2008, pp. 4373–4376.
79. D. Moraru, M. Ben, and G. Gravier, “Experiments on speakertracking and segmentation in radio broadcast news,” in Proc. ICSLP, 2005.
80. C. Barras, X. Zhu, S. Meignier, and J. -L. Gauvain, “Improving speaker diarization,” in Proc. DARPA RT04, 2004.
81. H. Aronowitz, “Trainable speaker diarization,” in Proc. Interspeech, Aug. 2007, pp. 1861–1864.
82. H. Hung and G. Friedland, “Towards audio-visual on-line diarization of participants in group meetings,” in Proc. Workshop Multi-Camera and Multi-Modal Sensor Fusion Algorithms Applicat. -M2SFA2, Marseille, France, 2008.
83. G. Friedland and O. Vinyals, “Live speaker identification in conversations,” in Proc. MM′08: Proc. 16th ACM Int. Conf. Multimedia, New York, 2008, pp. 1017–1018.
84. G. Friedland, O. Vinyals, Y. Huang, and C. Muller, “Prosodic and other long-term features for speaker diarization,” IEEE Trans. Audio, Speech, Lang. Process., vol. 17, no. 5, pp. 985–993, Jul. 2009.
85. J. Luque, X. Anguera, A. Temko, and J. Hernando, “Speaker diarization for conference room: The UPC RT07s evaluation system,” in Proc. Multimodal Technol. Perception of Humans: Int. Eval. Workshops CLEAR 2007 and RT 2007, Baltimore, MD, May 8-11, 2007, Revised Selected Papers, Berlin, Heidelberg: Springer-Verlag, 2008, pp. 543–553.
86. J. Pardo, X. Anguera, and C. Wooters, “Speaker diarization for multiple distant microphone meetings: Mixing acoustic features and interchannel time differences,” in Proc. Interspeech, 2006.
87. G. Lathoud and I. M. Cowan, “Location based speaker segmentation,” in Proc. ICASSP, 2003, vol. 1, pp. 176–179.
88. D. Ellis and J. C. Liu, “Speaker turn detection based on between-chan-nels differences,” in Proc. ICASSP, 2004.
89. J. Ajmera, G. Lathoud, and L. McCowan, “Clustering and segmenting speakers and their locations in meetings,” in Proc. ICASSP, 2004, vol. 1, pp. 605–608.
90. J. M. Pardo, X. Anguera, and C. Wooters, “Speaker diarization for multiple distant microphone meetings: Mixing acoustic features and inter-channel time differences,” in Proc. Interspeech, 2006.
91. J. Pardo, X. Anguera, and C. Wooters, “Speaker diarization for mul-tiple-distant-microphone meetings using several sources of information,” IEEE Trans. Comput., vol. 56, no. 9, pp. 1212–1224, Sep. 2007.
92. N. W. D. Evans, C. Fredouille, and J. -F. Bonastre, “Speaker diarization using unsupervised discriminant analysis of inter-channel delay features,” in Proc. ICASSP, Apr. 2009, pp. 4061–4064.
93. M. Wölfel, Q. Yang, Q. Jin, and T. Schultz, “Speaker identification using warped MVDR cepstral features,” in Proc. Interspeech, 2009.
94. E. Shriberg, “Higher-level features in speaker recognition,” in Speaker Classification I, C. MÜller, Ed. Berlin, Heidelberg, Germany: Springer, 2007, vol. 4343, Lecture Notes in Artificial Intelligence.
95. D. Imseng and G. Friedland, “Tuning-robust initialization methods for speaker diarization,” IEEE Trans. Audio, Speech, Lang. Process., vol. 18, no. 8, pp. 2028–2037, Nov. 2010.
96. D. Imseng and G. Friedland, “Robust speaker diarization for short speech recordings,” in Proc. IEEE Workshop Autom. Speech Recognit. Understand., Dec. 2009, pp. 432–437.
97. E. Shriberg, A. Stolcke, and D. Baron, “Observations on overlap: Findings and implications for automatic processing of multi-party conversations,” in Proc. Eurospeech′01, Aalborg, Denmark, 2001, pp. 1359–1362.
98. O. Çetin and E. Shriberg, “Speaker overlaps and ASR errors in meetings: Effects before, during, and after the overlap,” in Proc. ICASSP, Toulouse, France, 2006, pp. 357–360.
99. K. Boakye, B. Trueba-Hornero, O. Vinyals, and G. Friedland, “Overlapped speech detection for improved speaker diarization in multiparty meetings,” in Proc. ICASSP, 2008, pp. 4353–4356.
100. B. Trueba-Hornero, “Handling overlapped speech in speaker diariza-tion,” M. S. thesis, Univ. Politecnica de Catalunya, Barcelona, Spain, 2008.
101. K. Boakye, “Audio segmentation for meetings speech processing,” Ph. D. dissertation, Univ. of California, Berkeley, 2008.
102. S. Otterson and M. Ostendorf, “Efficient use of overlap information in speaker diarization,” in Proc. ASRU, Kyoto, Japan, 2007, pp. 686–686.
103. B. E. D. Kingsbury, N. Morgan, and S. Greenberg, “Robust speech recognition using the modulation spectrogram,” Speech Commun., vol. 25, no. 1-3, pp. 117–132, 1998.
104. H. J. Nock, G. Iyengar, and C. Neti, “Speaker localization using audiovisual synchrony: An empirical study,” Lecture Notes in Comput. Sci., vol. 2728, pp. 565–570, 2003.
105. C. Zhang, P. Yin, Y. Rui, R. Cutler, and P. Viola, “Boosting-based multimodal speaker detection for distributed meetings,” in Proc. IEEE Int. Workshop Multimedia Signal Process. (MMSP), 2006, pp. 86–91.
106. A. Noulas and B. J. A. Krose, “On-line multi-modal speaker diarization,” in Proc. 9th Int. Conf. Multimodal Interfaces ICMI ′07, New York, 2007, pp. 350–357.
107. Z. Ghahramani and M. I. Jordan, “Factorial hidden Markov models,” Mach. Learn., vol. 29, pp. 245–273, Nov. 1997.
108. A. K. Noulas, G. Englebienne, and B. J. A. Krose, “Mutimodal speaker diarization,” IEEE Trans. Pattern Anal Mach. Intell., 2011, preprint, to be published.
109. S. Tamura, K. Iwano, and S. Furui, “Multi-modal speech recognition using optical-flow analysis for lip images,” Real World Speech Process., vol. 36, no. 2-3, pp. 117–124, 2004.
110. T. Chen and R. Rao, “Cross-modal prediction in audio-visual communication,” in Proc. ICASSP, 1996, vol. 4, pp. 2056–2059.
111. J. W. Fisher, T. Darrell, W. T. Freeman, and P. A. Viola, “Learningjoint statistical models for audio-visual fusion and segregation,” in Proc. NIPS, 2000, pp. 772–778.
112. J. W. Fisher and T. Darrell, “Speaker association with signal-level audiovisual fusion,” IEEE Trans. Multimedia, vol. 6, no. 3, pp. 406–413, Jun. 2004.
113. R. Rao and T. Chen, “Exploiting audio-visual correlation in coding of talking head sequences,” in Proc. Int. Picture Coding Symp., Mar. 1996.
114. M. Siracusa and J. Fisher, “Dynamic dependency tests for audio-visual speaker association,” in Proc. ICASSP, Apr. 2007, pp. 457–460.
115. E. K. Patterson, S. Gurbuz, Z. Tufekci, and J. N. Gowdy, “CUAVE: A new audio-visual database for multimodal human-computer interface research,” in Proc. ICASSP, 2002, pp. 2017–2020.
116. D. McNeill, Language and Gesture. New York: Cambridge Univ. Press, 2000.
117. H. Vajaria, T. Islam, S. Sarkar, R. Sankar, and R. Kasturi, “Audio segmentation and speaker localization in meeting videos,” in Proc. 18th Int. Conf. Pattern Recognit. (ICPR′06), 2006, vol. 2, pp. 1150–1153.
118. H. Hung, Y. Huang, C. Yeo, and D. Gatica-Perez, “Associating audiovisual activity cues in a dominance estimation framework,” in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognition (CVPR) Workshop Human Communicative Behavior, Anchorage, AK, 2008, pp. 1–6.
119. N. Campbell and N. Suzuki, “Working with very sparse data to detect speaker and listener participation in a meetings corpus,” in Proc. Workshop Programme, May 2006, vol. 10.
120. G. Friedland, H. Hung, and C. Yeo, “Multimodal speaker diarization of real-world meetings using compressed-domain video features,” in Proc. ICASSP, Apr. 2009, pp. 4069–4072.
121. G. Friedland, C. Yeo, and H. Hung, “Visual speaker localization aided by acoustic models,” in Proc. 17th ACMInt. Conf. Multimedia MM′09:, New York, 2009, pp. 195–202.
122. S. Meignier, D. Moraru, C. Fredouille, J. -F. Bonastre, and L. Besacier, “Step-by-step and integrated approaches in broadcast news speaker diarization,” in Proc. CSL, Sel. Papers from Speaker Lang. Recognit. Workshop (Odyssey′04), 2006, pp. 303–330.
123. D. Vijayasenan, F. Valente, and H. Bourlard, “Combination of ag-glomerative and sequential clustering for speaker diarization,” in Proc. ICASSP, Las Vegas, NV, 2008, pp. 4361–4364.
124. E. El-Khoury, C. Senac, and S. Meignier, “Speaker diarization: Combination of the LIUM and IRIT systems,” in Internal Report, 2008.
125. V. Gupta, P. Kenny, P. Ouellet, G. Boulianne, and P. Dumouchel, “Combining Gaussianized/non-Gaussianized features to improve speaker diarization of telephone conversations,” in IEEE Signal Process. Lett., Dec. 2007, vol. 14, no. 12, pp. 1040–1043.
126. T. S. Ferguson, “A Bayesian analysis of some nonparametric problems,” Ann. Statist., vol. 1, no. 2, pp. 209–230, 1973.
127. F. Valente, “Infinite models for speaker clustering,” in Proc. Int. Conf. Spoken Lang. Process., 2006, iDIAP-RR 06-19.
128. Y. W. Teh, M. I. Jordan, M. J. Beal, and D. M. Blei, “Hierarchical Dirichlet processes,” J. Amer. Statist. Assoc., vol. 101, no. 476, pp. 1566–1581, 2006.
129. E. B. Fox, E. B. Sudderth, M. I. Jordan, and A. S. Willsky, “An HDP-HMM for systems with state persistence,” in Proc. ICML, Jul. 2008.
130. M. Huijbregts and C. Wooters, “The blame game: Performance analysis of speaker diarization system components,” in Proc. Interspeech, Aug. 2007, pp. 1857--1860.