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A Network-based End-to-End Trainable Task-oriented Dialogue System…
mi.eng.cam.ac.uk/~sjy/papers/wgmv17.pdf20 Feb 2018: 50.00 24.39 25.61Performance 43.90 25.61 30.49. -
Use of Deep Learning in Free Speaking Non-native English Assessment
mi.eng.cam.ac.uk/~mjfg/ALTA/presentations/TSD2021_Knill.pdf21 Feb 2022: 24/56. Deep Density Network-based Grader [1, 7]. • Deep Density Networks predict parameters of a distribution. -
Latent Intention Dialogue Models Tsung-Hsien Wen 1 * Yishu ...
mi.eng.cam.ac.uk/~sjy/papers/wmby17.pdf20 Feb 2018: goodbye. ( 1 0.24) you are welcome. goodbye. ( 85 0.19) is there anything else i can help you with? -
IEEE SIGNAL PROCESSING MAGAZINE [128] MAY 2010 This article ...
mi.eng.cam.ac.uk/~sjy/papers/youn10.pdf20 Feb 2018: THE HIDDEN INFORMATION STATE SYSTEMA block diagram of the HIS system is shown in Figure 13 [23], [24]. ... The history states record grounding and query status information but the details are not relevant here (see [24]). -
williams2005continuous06
mi.eng.cam.ac.uk/~sjy/papers/wipy05c.pdf20 Feb 2018: 1)(|( erruincorrecterrucorrect pacppacp = (24). In the MDP context, we assume the confidence score buckets are formed without access to a prior. )( -
Kate Knill ALTA Institute, Cambridge University Engineering…
mi.eng.cam.ac.uk/~kmk/presentations/Knill_UKSpeech2023_Keynote.pdf19 Jun 2023: conversational assessment. 24. Applying Foundation Models to Auto-marking: Neural Text Grader. -
Machine Intelligence Laboratory
mi.eng.cam.ac.uk/Main/GMT_EqnSurfIn the Windows version this will be saved in uncompressed 24-bit. -
Roberto Cipolla - Professor of Information Engineering
mi.eng.cam.ac.uk/~cipolla/professional.htmJuly 23-24, 1997. Organiser and Co-Chair of the European Conference on Computer Vision 1996,. -
Roberto Cipolla - Professor of Information Engineering
mi.eng.cam.ac.uk/~cipolla/publications.htmImage and Vision Computing, 24(6):639-647, June 2006. O. Arandjelovic and R. -
Abstract for hain_icslp00
mi.eng.cam.ac.uk/reports/abstracts/hain_icslp00.html27 Jul 2020: Experiments on the Resource Management (RM) corpus and a subset of the Switchboard corpus show that, relative to standard HMM baseline, a reduction word error rate (WER) of 24.3% relative
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