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Capturing Temporal Dependencies Through Future Prediction for CNN-Based Audio Classifiers., , , and . ICASSP, page 101-105. IEEE, (2021)Capturing High-Level Semantic Correlations via Graph for Multimodal Sentiment Analysis., , , , and . IEEE Signal Process. Lett., (2024)Sparse Decomposition for Signal Periodic Model Over Complex Exponential Dictionary., and . IEEE Signal Process. Lett., 23 (12): 1858-1861 (2016)A new framework for robust speech recognition in complex channel environments., , , and . Digit. Signal Process., (2014)Online Learning for Classification of Low-rank Representation Features and Its Applications in Audio Segment Classification, , , and . CoRR, (2011)Sentiment Knowledge Enhanced Self-supervised Learning for Multimodal Sentiment Analysis., , , , and . ACL (Findings), page 12966-12978. Association for Computational Linguistics, (2023)Convolutional Grid Long Short-Term Memory Recurrent Neural Network for Automatic Speech Recognition., , and . ICONIP (5), volume 1143 of Communications in Computer and Information Science, page 718-726. Springer, (2019)A Fast Audio Retrieval Method Based on Negativity Judgment., , , and . IIH-MSP, page 1156-1159. IEEE Computer Society, (2009)Sharpe Ratio-Oriented Active Trading: A Learning Approach., , and . MICAI, volume 2313 of Lecture Notes in Computer Science, page 331-339. Springer, (2002)Heterogeneous mixture models using sparse representation features for applause and laugh detection., , and . MLSP, page 1-5. IEEE, (2011)