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A NEURAL NETWORK BASED, SPEAKER INDEPENDENT, LARGE…
mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/wernicke_eurospeech93.pdf9 Aug 2005: 1.3. ComputingThe HMM-ANN approach is very computationally expensive.The networks currently require about 1013 floating point op-erations to train and future estimates of the required computepower is one -
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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/yow_tr249.pdf9 Aug 2005: qp> _ kB1&('10/?@,<'rQ?@>@=s=#?)65k ;1>A&t8Q0<=M)u vKaUwx. op'-0<DF65'C8! #"$. %&('),-.'0/2143 -
Department of EngineeringUniversity of Cambridge ����� ��� �� ��� ...
mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/harpur_thesis.pdf9 Aug 2005: Department of EngineeringUniversity of Cambridge! " $#%&' ( ) " ,%-.) / 0 213. George Francis HarpurQueens’ College. February 1997. A dissertation submitted forthe degree of Doctor of Philosophy. at the University of Cambridge. Summary. The -
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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/syn_thesis.pdf9 Aug 2005: F! d(e 2Df1 /ghi 2D'! 13@;!e 4j"$ 2kj 2 4# l69<a Dm690M%n op)>&EHGIbJqrs 0. -
TWO-WAY CLUSTER VOTING TO IMPROVE SPEAKER DIARISATION PERFORMANCE S.…
mi.eng.cam.ac.uk/reports/svr-ftp/tranter_icassp05.pdf25 Mar 2005: it isalso possible to generate the CVOS members directly from the op-timum speaker mapping between the two inputs. -
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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/malis_eccv00.pdf9 Aug 2005: " #$% #&')(,%-&-./0 #1%2%-&-3145 6789. ,9:0;) ". <>=-?A@CB,D4EA?GFHDJIKML@JNPO-QSRS@7TH?AU2@VEAEAD. WXZY%[XV] ]_[XZYa]_bdc-feg+]_X4ehVic-g&jJ[lkJY%]mHXZ[no]_pf[qesrt2uVgbZ[XZY-ev%Xxwyef] ]_ehZiz{'| }0ic-g&jJ[lkJY%]. -ZyP%Joo%y-o-yf%_yPoyo -
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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/waterhouse_nips94.pdf9 Aug 2005: E? P@$#WT $ F @E> "!I $&% &> & @ #" OP@Q;R!# @ AW$FH "KR $ W I E$%#@E! ... diiF:«0JN?CF=eH. Ò º D?E"&% & & % %EA D#OP &>? & G%;FH"JLK'& &&O )"E @?& I @XO $!#& @E>.$!#&&?VPPU! " $%&! " -
Automatic Face Recognition for Film Character Retrieval in…
mi.eng.cam.ac.uk/reports/svr-ftp/oa214_CVPR_2005_paper2.pdf8 Aug 2005: 2.5.1 Improving Registration. In the registration method proposed in Section 2.2, the op-timal warp parameters were estimated from 3 point corre-spondences in 2D. -
SVMS, SCORE-SPACES AND MAXIMUM MARGIN STATISTICAL MODELS M.J.F. Gales …
mi.eng.cam.ac.uk/~mjfg/BeyondHMM.pdf15 Jun 2005: This comes directly fromequation 19. It is interesting to contrast this to MMI training [11].In MMI training the average posterior of the correct label is op-timised. -
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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/holden_tr161.pdf9 Aug 2005: "!#$% & ' ($) , -. 0/213546. 798;:=<>@?#<>&ABDC;A-EGFH>)8>IBKJLNM.O5J):=M.A 8PJ8QR+>IL.ETSUR:=B=VWX:=V B=MN8YZMN8;[MN8>]J-B%LC_>)M.Y<:K>]Q. abA88>&WX:=M.A 8 M.cU:edf>g:ihbABKj c. k)lmXnpoq-rsXtvu-lnw. xyz|{G}= Tz|G}=GqvD&. mXn]m%X]DX%.
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