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Abstract
In this paper, intelligent audio signal processing examples are shortly described. The focus is, however, on the machine learning approach and datasets needed, especially for deep learning models. Years of intense research produced many important results in this area; however, the goal of fully intelligent signal processing, characterized by its autonomous acting, is not yet achieved. Therefore, a review of state-of-the-art concerning this area is given. The aspect of showing the importance of acquiring an appropriate dataset containing audio samples dedicated to the task is also shown. The paper starts with samples of audio-related datasets resulting from the search engine inquiry. Then, examples of research studies along with results are given. Also, several works carried out by the author and her collaborators are presented. Some thoughts on future work are included with answering a question of whether annotated datasets are still needed.
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- Publication version
- Accepted or Published Version
- License
- Copyright (2022 The Author(s), under exclusive license to Springer Nature Switzerland AG)
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Details
- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Language:
- English
- Publication year:
- 2022
- Bibliographic description:
- Kostek B.: Intelligent Audio Signal Processing − Do We Still Need Annotated Datasets?// / : , 2022,
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/978-3-031-21967-2_55
- Verified by:
- Gdańsk University of Technology
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