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Titlebook: Machine Learning for Multimodal Interaction; 4th International Wo Andrei Popescu-Belis,Steve Renals,Hervé Bourlard Conference proceedings 2

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樓主: dentin
11#
發(fā)表于 2025-3-23 13:26:20 | 只看該作者
Integrating Semantics into Multimodal Interaction Patternsd the semantics of the command being issued by the user (4 types of commands), shedding new light on previous research findings that assign a unique temporal integration pattern to any given subject regardless of the communication taking place.
12#
發(fā)表于 2025-3-23 16:20:12 | 只看該作者
Using Prosodic Features in Language Models for Meetingsnt variable to represent similar prosodic patterns shared by groups of words. Four-fold cross-validation experiments on the ICSI Meeting Corpus show that exploiting prosody for language modeling can significantly reduce the perplexity, and also have marginal reductions in word error rate.
13#
發(fā)表于 2025-3-23 19:15:28 | 只看該作者
Posterior-Based Features and Distances in Template Matching for Speech Recognition we also study posterior-based local distances, these result more effective than traditional Euclidean distance. Experiments on Phonebook database support the idea that posterior features with a proper local distance can yield competitive results.
14#
發(fā)表于 2025-3-23 22:50:13 | 只看該作者
15#
發(fā)表于 2025-3-24 03:59:40 | 只看該作者
16#
發(fā)表于 2025-3-24 07:28:40 | 只看該作者
Gaussian Process Latent Variable Models for Human Pose Estimationouettes by temporal consistency. The model has only two free parameters and has several advantages over both regression approaches and other generative methods. In addition to the application shown in this paper the suggested model is easily extended to multiple observation spaces without constraints on type.
17#
發(fā)表于 2025-3-24 13:33:42 | 只看該作者
18#
發(fā)表于 2025-3-24 16:14:08 | 只看該作者
19#
發(fā)表于 2025-3-24 21:29:45 | 只看該作者
20#
發(fā)表于 2025-3-24 23:16:25 | 只看該作者
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