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Speech Sentiment Analysis via Pre-Trained Features from End-to-End ASR Models.

, , , , and . ICASSP, page 7149-7153. IEEE, (2020)

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A Large Scale Speech Sentiment Corpus., , , , , and . LREC, page 6549-6555. European Language Resources Association, (2020)Hyper-parameter Tuning under a Budget Constraint., , , and . IJCAI, page 5744-5750. ijcai.org, (2019)Kernel Approximation Methods for Speech Recognition., , , , , , , , , and 2 other author(s). J. Mach. Learn. Res., (2019)Improving the Fusion of Acoustic and Text Representations in RNN-T., , , , and . ICASSP, page 8117-8121. IEEE, (2022)Exploring Targeted Universal Adversarial Perturbations to End-to-End ASR Models., , , and . Interspeech, page 3460-3464. ISCA, (2021)Selecting β-Divergence for Nonnegative Matrix Factorization by Score Matching., , and . ICANN (2), volume 7553 of Lecture Notes in Computer Science, page 419-426. Springer, (2012)Improving Streaming Automatic Speech Recognition with Non-Streaming Model Distillation on Unsupervised Data., , , , , , , , , and . ICASSP, page 6558-6562. IEEE, (2021)Direct Large Language Model Alignment Through Self-Rewarding Contrastive Prompt Distillation., , , , , , , and . CoRR, (2024)Speech Sentiment Analysis via Pre-Trained Features from End-to-End ASR Models., , , , and . ICASSP, page 7149-7153. IEEE, (2020)Learning compact recurrent neural networks., , and . ICASSP, page 5960-5964. IEEE, (2016)