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auDeep: Unsupervised Learning of Representations from Audio with Deep Recurrent Neural Networks

arXiv 1712.04382 ↗First posted 12 Dec 2017cs.SD eess.AScited by 16

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Abstract (arXiv)

auDeep is a Python toolkit for deep unsupervised representation learning from acoustic data. It is based on a recurrent sequence to sequence autoencoder approach which can learn representations of time series data by taking into account their temporal dynamics. We provide an extensive command line interface in addition to a Python API for users and developers, both of which are comprehensively documented and publicly available at https://github.com/auDeep/auDeep. Experimental results indicate that auDeep features are competitive with state-of-the art audio classification.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Dec 2017.

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Citing papers per year: 2021: 7; 2022: 6; 2023: 2; 2024: 1.

16 papers.

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  1. 2021The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 Cough, COVID-19 Speech, Escalation & Primatescited by 32
  2. 2022Vision+X: A Survey on Multimodal Learning in the Light of Datacited by 22
  3. 2021Detecting Dementia from Speech and Transcripts using Transformerscited by 13
  4. 2021DeepSpectrumLite: A Power-Efficient Transfer Learning Framework for Embedded Speech and Audio Processing from Decentralised Datacited by 12
  5. 2023The ACM Multimedia 2023 Computational Paralinguistics Challenge: Emotion Share & Requestscited by 8
  6. 2021DECAR: Deep Clustering for learning general-purpose Audio Representationscited by 7
  7. 2021On the Impact of Word Error Rate on Acoustic-Linguistic Speech Emotion Recognition: An Update for the Deep Learning Eracited by 5
  8. 2023Context-aware attention layers coupled with optimal transport domain adaptation and multimodal fusion methods for recognizing dementia from spontaneous speechcited by 5
  9. 2022The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitoescited by 4
  10. 2022A Summary of the ComParE COVID-19 Challengescited by 2
  11. 2021Guided-GAN: Adversarial Representation Learning for Activity Recognition with Wearablescited by 1
  12. 2022A Study on Broadcast Networks for Music Genre Classificationcited by 1
4 more
  1. 2024autrainer: A Modular and Extensible Deep Learning Toolkit for Computer Audition Taskscited by 1
  2. 2021Underwater Acoustic Networks for Security Risk Assessment in Public Drinking Water Reservoirscited by 0
  3. 2022DeLoRes: Decorrelating Latent Spaces for Low-Resource Audio Representation Learningcited by 0
  4. 2022Interpretable Acoustic Representation Learning on Breathing and Speech Signals for COVID-19 Detectioncited by 0