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Titlebook: Advances in Speech and Language Technologies for Iberian Languages; IberSPEECH 2012 Conf Doroteo Torre Toledano,Alfonso Ortega Giménez ,Dan

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樓主: dilate
21#
發(fā)表于 2025-3-25 06:26:56 | 只看該作者
Computer and Information Sciencethe output of a perfect segmentation system (oracle boundaries). It can be seen how FA improves the classification results compared to HMM/GMM. Also, the first experiments of an on-building FA segmentation system are reported suggesting the need to improve the channel compensation over some classes.
22#
發(fā)表于 2025-3-25 08:09:35 | 只看該作者
23#
發(fā)表于 2025-3-25 11:47:47 | 只看該作者
Factor Analysis Segmentation and Classification in Broadcast News Domainthe output of a perfect segmentation system (oracle boundaries). It can be seen how FA improves the classification results compared to HMM/GMM. Also, the first experiments of an on-building FA segmentation system are reported suggesting the need to improve the channel compensation over some classes.
24#
發(fā)表于 2025-3-25 16:36:04 | 只看該作者
Merging Intention and Emotion to Develop Adaptive Dialogue Systemsived as an intermediate phase between natural language understanding and dialogue management in the architecture of these systems. We have applied and evaluated our method in the UAH system, for which the evaluation results show that merging both sources of information improves system performance as well as its perceived quality.
25#
發(fā)表于 2025-3-25 23:32:38 | 只看該作者
26#
發(fā)表于 2025-3-26 00:29:43 | 只看該作者
27#
發(fā)表于 2025-3-26 05:13:57 | 只看該作者
On the Influence of Automatic Segmentation and Clustering in Automatic Speech Recognitionranscrigal, and results show that the speaker diarization system presented in this work is suitable as a previous step to ASR, as the performance is almost the same as the obtained when using manual segmentation and clustering.
28#
發(fā)表于 2025-3-26 09:30:21 | 只看該作者
29#
發(fā)表于 2025-3-26 14:09:54 | 只看該作者
30#
發(fā)表于 2025-3-26 19:42:23 | 只看該作者
A Multilingual SLU System Based on Semantic Decoding of Graphs of Wordsed. The graph of words generated in this phase is the input to the semantic decoding algorithm specifically designed to combine statistical models and graphs of words. Some experiments that show the good behavior of the proposed approach are also presented.
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