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Statistical Pattern Processing - Module 4F10
mi.eng.cam.ac.uk/~mjfg/local/4F10/24 Nov 2016: matlab.zip matlab routines (iris example data). mlpdemo - mlp training on iris data [train: iris_tra, tests: iris_tes]. ... gmmdemo - gmm training on iris data [train: iris_tra, tests: iris_tes]. -
Machine Learning of Level and Progression in Spoken EAL ...
mi.eng.cam.ac.uk/~kmk/presentations/CEP_Feb2016_Knill.pdf12 May 2016: Business Language Testing Service (BULATS) Spoken Tests. • Example of a test of communication skills A. ... Use automatic grader • for grading practice tests/learning process • in combination with human graders. • -
2014 Science Week lecture
mi.eng.cam.ac.uk/~cipolla/archive/Presentations/2016-Computer-Vision-Intro.pdf22 Feb 2016: SegNet predictions on unseen test images - DEMO. SegNet – Real-time DEMO. -
Machine Learning of Level and Progression in Second/Additional…
mi.eng.cam.ac.uk/~kmk/presentations/UBham_May2016_Knill.pdf12 May 2016: Business Language Testing Service (BULATS) Spoken Tests. • Example of a test of communication skills A. ... Statistical Parser Features. • Parser features from RASP system improve grades for written tests. • -
Combining I-vector Representation and Structured Neural Networks for…
mi.eng.cam.ac.uk/~mjfg/icassp16_wu.pdf5 Apr 2016: English Broadcast News (BN) transcription task.Two distinct sets of test data are examined. ... The first from the BNtask, yields test data acoustically matched to the training data. -
Knill_IS2014_slides.dvi
mi.eng.cam.ac.uk/~kmk/presentations/Interspeech2014_Sep14_Knill.pdf12 May 2016: Training and Test Languages. Language Release # MissingPhones Tones. Cantonese IARPA-babel101-v0.4c — —Assamese IARPA-babel102b-v0.5a — —Bengali IARPA-babel103b-v0.4b 12 —Pashto IARPA-babel104b-v0.4aY — —Turkish -
Investigation of back-off based interpolation between Recurrent…
mi.eng.cam.ac.uk/~mjfg/asru15-chen.pdf11 Mar 2016: A development data set of 70kwords was used parameter tuning. A separate 79k word test test wasused for performance evaluation. ... 184. Table 2. PPL results on test set of PTB corpusn-gralm LM back-off level. -
SYSTEM COMBINATION WITH LOG-LINEAR MODELS J. Yang, C. Zhang, ...
mi.eng.cam.ac.uk/~mjfg/yang_ICASSP16.pdf12 Jul 2016: conditions. The test set is based on the development set of 1992November NIST evaluation, and it is artificially corrupted by using6 types of noise under 2 channel conditions. ... The mean of the prior is. System Criterion Test Set WER(%) Avg.A B C -
System Combination with Log-linear Models
mi.eng.cam.ac.uk/~mjfg/icassp16_yang.pdf5 Apr 2016: 5677. conditions. The test set is based on the development set of 1992November NIST evaluation, and it is artificially corrupted by using6 types of noise under 2 channel conditions. ... The mean of the prior is. System Criterion Test Set WER(%) Avg.A B C -
STRUCTURED DISCRIMINATIVE MODELS USING DEEP NEURAL-NETWORK FEATURES…
mi.eng.cam.ac.uk/~mjfg/vandalen_ASRU15.pdf12 Jul 2016: The test set is an ar-tificially corrupted subset of the development set of 1992 NovemberNIST evaluation using 6 types of noise under two microphone con-ditions with SNRs in the ... For each language, the training data (in the “verylimited language
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