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TT+GT at TRECVID 2010 Workshop.

, , , , , , и . TRECVID, National Institute of Standards and Technology (NIST), (2010)

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Hsun-Hui Lee

Yen-Hui Lee

Elion Chin

Erika Chin

Yen-Lee Bernice Chin Jen Sem

 

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A Study on Music Genre Classification Based on Universal Acoustic Models., и . ISMIR, стр. 89-94. (2006)Space-and-speaker-aware acoustic modeling with effective data augmentation for recognition of multi-array conversational speech., , , , и . Speech Commun., (сентября 2023)Acoustics-guided evaluation (AGE): a new measure for estimating performance of speech enhancement algorithms for robust ASR., , и . CoRR, (2018)Improving Deep Neural Network Based Speech Synthesis through Contextual Feature Parametrization and Multi-Task Learning., , , , и . J. Signal Process. Syst., 90 (7): 1025-1037 (2018)An Information-Extraction Approach to Speech Processing: Analysis, Detection, Verification, and Recognition., и . Proc. IEEE, 101 (5): 1089-1115 (2013)A Regression Approach to Speech Enhancement Based on Deep Neural Networks., , , и . IEEE ACM Trans. Audio Speech Lang. Process., 23 (1): 7-19 (2015)A Four-Stage Data Augmentation Approach to ResNet-Conformer Based Acoustic Modeling for Sound Event Localization and Detection., , , , , и . IEEE ACM Trans. Audio Speech Lang. Process., (2023)A voice user interface demonstration system for mexican Spanish., , , и . ICSLP, ISCA, (1998)Predictive adaptation and compensation for robust speech recognition., и . ICSLP, ISCA, (1998)Bayesian learning of the parameters of discrete and tied mixture HMMs for speech recognition., , и . EUROSPEECH, стр. 1567-1570. ISCA, (1993)