Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Subasingha Shaminda Subasingha"'
Publikováno v:
Subasingha, S, Murthi, MN & Andersen, S V 2009, ' Gaussian Mixture Kalman Predictive Coding of Line Spectral Frequencies ', IEEE Transactions on Audio Speech and Language Processing, vol. 17, no. 2, pp. 379-391 . https://doi.org/10.1109/TASL.2008.2008735
Gaussian mixture model (GMM)-based predictive coding of line spectral frequencies (LSFs) has gained wide acceptance. In such coders, each mixture of a GMM can be interpreted as defining a linear predictive transform coder. In this paper, we use Kalma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7456a0ab7803afcef54aecee0d398c5
https://doi.org/10.1109/tasl.2008.2008735
https://doi.org/10.1109/tasl.2008.2008735
Autor:
Daniel J. Sinder, Jeremie Lecomte, Benjamin Schubert, Duminda A. Dewasurendra, Atti Venkatraman S, Venkata Subrahmanyam Chandra Sekhar Chebiyyam, Subasingha Shaminda Subasingha, Lei Miao, Vivek Rajendran, Imre Varga, Venkatesh Krishnan, Xingtao Zhang
Publikováno v:
ICASSP
A highly error resilient mode of the newly standardized 3GPP EVS speech codec is described. Compared to the AMR-WB codec and other conversational codecs, the EVS channel aware mode offers significantly improved error resilience in voice communication
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ff8d148fff19a3091f832cb57f99aac
https://doi.org/10.1109/icassp.2015.7179066
https://doi.org/10.1109/icassp.2015.7179066
Autor:
Duminda A. Dewasurendra, Daniel J. Sinder, Volodya Grancharov, Venkata Subrahmanyam Chandra Sekhar Chebiyyam, Subasingha Shaminda Subasingha, Harald Pobloth, Atti Venkatraman S, Jon Gibbs, Vivek Rajendran, Imre Varga, Lei Miao, Venkatesh Krishnan
Publikováno v:
ICASSP
This paper describes the time-domain bandwidth extension (TBE) framework employed to code wideband and super-wideband speech in the newly standardized 3GPP EVS codec. The TBE algorithm uses a nonlinear harmonic modeling technique that incorporates pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9ecc5b3f5012c171f184417dcc609f48
https://doi.org/10.1109/icassp.2015.7179109
https://doi.org/10.1109/icassp.2015.7179109
Autor:
Kei Kikuiri, Ho-Sang Sung, Jeremie Lecomte, Wang Bin, Julien Faure, Tommy Vaillancourt, Stefan Bruhn, Ke Peng, Subasingha Shaminda Subasingha
Publikováno v:
ICASSP
EVS, the newly standardized 3GPP Codec for Enhanced Voice Services (EVS) was developed for mobile services such as VoLTE, where error resilience is highly essential. The presented paper outlines all aspects of the advances brought during the EVS deve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::290a82b9b6717068c0849d9d5a71ff5f
https://doi.org/10.1109/icassp.2015.7179065
https://doi.org/10.1109/icassp.2015.7179065
Publikováno v:
DPS
Subasingha, S, Murthi, M N & Andersen, S V 2009, A Kalman filtering approach to GMM predictive coding of LSFS for packet loss conditions . in Proceedings of the 16th international conference on Digital Signal Processing . IEEE Press, pp. 434-439, DSP 2009: 16th International Conference on Digital Signal Processing, Santorini, Greece, 05/07/2009 . https://doi.org/10.1109/ICDSP.2009.5201111
Subasingha, S, Murthi, M N & Andersen, S V 2009, A Kalman filtering approach to GMM predictive coding of LSFS for packet loss conditions . in Proceedings of the 16th international conference on Digital Signal Processing . IEEE Press, pp. 434-439, DSP 2009: 16th International Conference on Digital Signal Processing, Santorini, Greece, 05/07/2009 . https://doi.org/10.1109/ICDSP.2009.5201111
Gaussian Mixture Model (GMM)-based vector quantization of Line Spectral Frequencies (LSFs) has gained wide acceptance in speech coding. In predictive coding of LSFs, the GMM approach utilizing Kalman filtering principles to account for quantization n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::718cc1ce2fb3ad4dc051743eef17fed0
https://doi.org/10.1109/icdsp.2009.5201111
https://doi.org/10.1109/icdsp.2009.5201111
Publikováno v:
Subasingha, S, Murthi, M N & Andersen, S V 2009, On GMM Kalman predictive coding of LSFS for packet loss . in IEEE International Conference on Acoustics, Speech and Signal Processing, 2009. ICASSP 2009 . IEEE, International Conference on Acoustics Speech and Signal Processing (ICASSP), pp. 4105-4108, IEEE International Conference on Acoustics, Speech and Signal Processing, 2009. ICASSP 2009, Taipei, Taiwan, Province of China, 24/04/2008 . https://doi.org/10.1109/ICASSP.2009.4960531
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::15474584d3ae1c332333d2421d086d68
https://vbn.aau.dk/da/publications/736d2ed0-05bc-11df-9046-000ea68e967b
https://vbn.aau.dk/da/publications/736d2ed0-05bc-11df-9046-000ea68e967b
Publikováno v:
2009 Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers.
Distributed Source Coding (DSC) has gained wide popularity in applications such as video coding and distributed sensor networks. However, DSC has not been widely explored for use in low delay, low bit rate applications such as quantization of speech
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::19dc379aa414d20733022475c4e11c62
https://doi.org/10.1109/acssc.2009.5469980
https://doi.org/10.1109/acssc.2009.5469980
Publikováno v:
ICASSP
Gaussian mixture model (GMM)-based predictive coding of line spectral frequencies (LSFs) has gained wide acceptance. In such coders, each mixture of a GMM can be interpreted as defining a linear predictive transform coder. In this paper we optimize e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae7642c92590a81b32f5b7cc0a03ef10
https://doi.org/10.1109/icassp.2008.4518725
https://doi.org/10.1109/icassp.2008.4518725
Autor:
Kamal Premaratne, J. Zhang, K. K.R.G.K. Hewawasam, Miroslav Kubat, Mei-Ling Shyu, Subasingha Shaminda Subasingha
Publikováno v:
Data Mining: Foundations and Practice ISBN: 9783540784876
Data Mining: Foundations and Practice
Data Mining: Foundations and Practice
This chapter introduces a belief theoretic method for classification from databases having class label ambiguities. It uses a set of association rules extracted from such a database. It is assumed that a training data set with an adequate number of p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f45ab5182434f47d6c4dea08414a27b5
https://doi.org/10.1007/978-3-540-78488-3_32
https://doi.org/10.1007/978-3-540-78488-3_32
Publikováno v:
SPIE Proceedings.
Numerous applications of topical interest call for knowledge discovery and classification from information that may be inaccurate and/or incomplete. For example, in an airport threat classification scenario, data from heterogeneous sensors are used t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c5a7d71387a98e64a070c24b371ad1a
https://doi.org/10.1117/12.603993
https://doi.org/10.1117/12.603993