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The NTT DCASE2020 Challenge Task 6 system: Automated Audio Captioning with Keywords and Sentence Length Estimation.

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Trilingual Semantic Embeddings of Visually Grounded Speech with Self-Attention Mechanisms., , , , , и . ICASSP, стр. 4352-4356. IEEE, (2020)Automatic Identification for Singing Style based on Sung Melodic Contour Characterized in Phase Plane., , , , и . ISMIR, стр. 393-398. International Society for Music Information Retrieval, (2009)SoundBeam: Target sound extraction conditioned on sound-class labels and enrollment clues for increased performance and continuous learning., , , , , и . CoRR, (2022)Multi-view and Multi-modal Event Detection Utilizing Transformer-based Multi-sensor fusion., , , и . CoRR, (2022)Acoustic scene analysis based on latent acoustic topic and event allocation., , , и . MLSP, стр. 1-6. IEEE, (2013)Effects of Word-Frequency Based Pre- and Post- Processings for Audio Captioning., , , , и . DCASE, стр. 190-194. (2020)Echo-Aware Adaptation of Sound Event Localization and Detection in Unknown Environments., , и . ICASSP, стр. 226-230. IEEE, (2022)Pair Expansion for Learning Multilingual Semantic Embeddings Using Disjoint Visually-Grounded Speech Audio Datasets., , , , , и . INTERSPEECH, стр. 1486-1490. ISCA, (2020)Guided Masked Self-Distillation Modeling for Distributed Multimedia Sensor Event Analysis., , , , , и . CoRR, (2024)Exploring Pre-trained General-purpose Audio Representations for Heart Murmur Detection., , , , и . CoRR, (2024)