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Titlebook: Advances in Speech and Language Technologies for Iberian Languages; IberSPEECH 2014 Conf Juan Luis Navarro Mesa,Alfonso Ortega,Doroteo T. T

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樓主: Causalgia
31#
發(fā)表于 2025-3-26 21:00:29 | 只看該作者
Haiyan Hu,Huoguo Zheng,Shihong Liud Total Variability (i-vector) strategies, respectively. Moreover, a simple fusion of the developed approaches and the reference systems has been performed. Some individual and fusion systems outperform the reference systems, obtaining ~ 17% of relative improvement in terms of .. for one of the challenging pairs.
32#
發(fā)表于 2025-3-27 01:15:52 | 只看該作者
Hongxu Wang,FuJin Zhang,Yunsheng Xufor acoustic modeling in a noisy automatic speech recognition environment. Experiments show that DMNs improve substantially the recognition accuracy over DNNs and other traditional techniques in both clean and noisy conditions on the TIMIT dataset.
33#
發(fā)表于 2025-3-27 09:18:07 | 只看該作者
Zhenqi Fan,Chunjing Si,Quanli Yangiques are compared within two different acoustic models: a standard HMM model and the CD-DNN-HMM model. The proposed method obtains improvements on WER of up to 14% relative with respect to a competitive baseline as well as outperforming slide adaptation.
34#
發(fā)表于 2025-3-27 12:18:25 | 只看該作者
35#
發(fā)表于 2025-3-27 16:32:22 | 只看該作者
36#
發(fā)表于 2025-3-27 19:18:30 | 只看該作者
Unsupervised Accent Modeling for Language Identificationing the test, each utterance is evaluated against all of them. The highest score of each language is selected to make decisions. The experiment was carried out on 6 languages of the 2011 NIST LRE dataset. For the 30 s condition, the relative improvement over the baseline was of 11%.
37#
發(fā)表于 2025-3-27 22:59:03 | 只看該作者
38#
發(fā)表于 2025-3-28 04:58:12 | 只看該作者
Confidence Measures in Automatic Speech Recognition Systems for Error Detection in Restricted Domainate the reliability of recognition results, discarding low confidence words at the output. These CM can be used as a tool for Unsupervised Learning Techniques, and also for helping human supervision of recognition results. If accurate enough, these CM would increase the usability as well as the robustness of speech applications.
39#
發(fā)表于 2025-3-28 08:54:16 | 只看該作者
Recognition of Distant Voice Commands for Home Applications in Portuguesehow that the strategies based on envelope-variance measure consistently outperformed the remaining methods investigated, and particularly, that channel selection strategies can be more convenient than baseline beamforming methods, such as delay-and-sum, for this type of multi-room scenarios.
40#
發(fā)表于 2025-3-28 13:55:50 | 只看該作者
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