Publications

Found 1074 results
Author Title [ Type(Desc)] Year
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Conference Paper
Stolcke, A., Ferrer L., Kajarekar S., Shriberg E., & Venkataraman A. (2005).  MLLR Transforms as Features in Speaker Recognition. Proceedings of the 9th European Conference on Speech Communication and Technology (Interspeech 2005-Eurospeech 2005). 2425-2428.
Kajarekar, S., Ferrer L., Sönmez K., Zheng J., Shriberg E., & Stolcke A. (2004).  Modeling NERFs for Speaker Recognition. Proceedings of the Speaker and Language Recognition Workshop (Odyssey 2004). 51-56.
Ee, C. Tien, Fonseca R., Kim S., Moon D., Tavakoli A., Culler D. E., et al. (2006).  A Modular Network Layer for Sensornets. Proceedings of the 7th Symposium on Operating Systems Design and Implementation (OSDI '06). 249-262.
Vinyals, O., & Friedland G. (2008).  Modulation Spectrogram Features for Speaker Diarization. Proceedings of the 9th Annual Conference of the International Speech Communication Association (Interspeech 2008). 630-633.
Fosler-Lussier, E. (1999).  Multi-Level Decision Trees for Static and Dynamic Pronunciation Models. Proceedings of the 6th European Conference on Speech Communication and Technology (Eurospeech '99).
Friedland, G., Hürst W.., & Knipping L. (2008).  Multimedia Education—Can We Find Unity in Diversity?. 1115-1116.
Friedland, G., Papadopoulos S., Bernd J., & Kompatsiaris Y. (2016).  Multimedia Privacy. Proceedings of the 2016 ACM Conference on Multimedia (MM '16). 1479-1480.
Lei, H., Choi J., & Friedland G. (2012).  Multimodal City-Verification on Flickr Videos Using Acoustic and Textual Features. 2273-2276.
Vinyals, O., Martin E., & Friedland G. (2010).  Multimodal Indoor Localization: An Audio-Wireless-Based Approach. 120-125.
Müller, C., & Friedland G. (2009).  Multimodal Interfaces for Automotive Applications (MIAA). 493-494.
Friedland, G., Vinyals O., & Darrell T. (2010).  Multimodal Location Estimation. 1245-1251.
Choi, J., Friedland G., Ekambaram V., & Ramchandran K. (2012).  Multimodal Location Estimation of Consumer Media – Dealing with Sparse Training Data. 43-48.
Friedland, G., Choi J., Lei H., & Janin A. (2011).  Multimodal Location Estimation on Flickr Videos.
Friedland, G., Hung H., & Yeo C. (2009).  Multi-Modal Speaker Diarization of Real-World Meeting Using Compressed-Domain Video Features. 4069-4072.
Knox, M. Tai, & Friedland G. (2010).  Multimodal Speaker Diarization Using Oriented Optical Flow Histograms. 290-293.
Richter, P., Wohlfart F., Vallina-Rodriguez N., Allman M., Bush R., Feldmann A., et al. (2016).  A Multi-perspective Analysis of Carrier-Grade NAT Deployment. Proceedings of ACM Internet Measurement Conference.
Gittens, A., Kottalam J., Yang J., Ringenburg M. F., Chhugani J., Racah E., et al. (2016).  A multi-platform evaluation of the randomized CX low-rank matrix factorization in Spark. Proceedings of the 5th International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics.
Cohen, M., Franco H., Morgan N., Rumelhart D., & Abrash V. (1992).  Multiple-State Context-Dependent Phonetic Modeling with MLPs. Proceedings of the Speech Research Symposium XII.
Friedrich, T., Horoba C., & Neumann F. (2009).  Multiplicative Approximations and the Hypervolume Indicator. 571-578.
Donoho, D.., Flesia A.. G., Shankar U., Paxson V., Coit J.., & Staniford S. (2002).  Multiscale Stepping-Stone Detection: Detecting Pairs of Jittered Interactive Streams by Exploiting Maximum Tolerable Delay. Proceedings of RAID.
Peters, N., Lei H., & Friedland G. (2012).  Name That Room: Room Identification Using Acoustic Features in a Recording. 841-844.
Friedland, G., Gottlieb L., & Janin A. (2010).  Narrative-Theme Navigation for Sitcoms Supported by Fan-Generated Scripts. 3-8.
Maier, G., Schneider F., & Feldmann A. (2011).  NAT Usage in Residential Broadband Networks.
Feldman, J., Trott S., & Khayrallah H. (2015).  Natural Language For Human Robot Interaction.
Hu, R., Xu H., Rohrbach M., Feng J., Saenko K., & Darrell T. (2016).  Natural Language Object Retrieval. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

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