mlsanityData to 14 Oct 2026

Direction of arrival estimation for multiple sound sources using convolutional recurrent neural network

arXiv 1710.10059 ↗First posted 27 Oct 2017cs.SD cs.LG eess.AScited by 27

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Abstract (arXiv)

This paper proposes a deep neural network for estimating the directions of arrival (DOA) of multiple sound sources. The proposed stacked convolutional and recurrent neural network (DOAnet) generates a spatial pseudo-spectrum (SPS) along with the DOA estimates in both azimuth and elevation. We avoid any explicit feature extraction step by using the magnitudes and phases of the spectrograms of all the channels as input to the network. The proposed DOAnet is evaluated by estimating the DOAs of multiple concurrently present sources in anechoic, matched and unmatched reverberant conditions. The results show that the proposed DOAnet is capable of estimating the number of sources and their respective DOAs with good precision and generate SPS with high signal-to-noise ratio.

Key facts. Cited by 27 papers in the map (data through 14 Oct 2026). First posted on arXiv 27 Oct 2017.

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Citing papers per year: 2021: 7; 2022: 5; 2023: 6; 2024: 3; 2025: 4; 2026: 2.

27 papers.

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  1. 2021A Survey of Sound Source Localization with Deep Learning Methodscited by 46
  2. 2022Egocentric Deep Multi-Channel Audio-Visual Active Speaker Localizationcited by 27
  3. 2022Sound Localization by Self-Supervised Time Delay Estimationcited by 18
  4. 2023Sound Localization from Motion: Jointly Learning Sound Direction and Camera Rotationcited by 18
  5. 2023Resilient Multiple Choice Learning: A learned scoring scheme with application to audio scene analysiscited by 12
  6. 2021PILOT: Introducing Transformers for Probabilistic Sound Event Localizationcited by 7
  7. 2021Exploiting Attention-based Sequence-to-Sequence Architectures for Sound Event Localizationcited by 6
  8. 2023LocSelect: Target Speaker Localization with an Auditory Selective Hearing Mechanismcited by 6
  9. 2024Winner-takes-all learners are geometry-aware conditional density estimatorscited by 6
  10. 2024TF-Mamba: A Time-Frequency Network for Sound Source Localizationcited by 5
  11. 2022MIMO-DoAnet: Multi-channel Input and Multiple Outputs DoA Network with Unknown Number of Sound Sourcescited by 4
  12. 2022Direction of Arrival Estimation of Sound Sources Using Icosahedral CNNscited by 3
15 more
  1. 2023Quaternion Convolutional Neural Networks: Current Advances and Future Directionscited by 3
  2. 2023Dual input neural networks for positional sound source localizationcited by 3
  3. 2021DeepAoANet: Learning Angle of Arrival from Software Defined Radios with Deep Neural Networkscited by 2
  4. 2021Data Fusion for Audiovisual Speaker Localization: Extending Dynamic Stream Weights to the Spatial Domaincited by 1
  5. 2022Iterative Sound Source Localization for Unknown Number of Sourcescited by 1
  6. 2025Spatial and Semantic Embedding Integration for Stereo Sound Event Localization and Detection in Regular Videoscited by 1
  7. 2025Integrating Spatial and Semantic Embeddings for Stereo Sound Event Localization in Videoscited by 1
  8. 2021What Makes Sound Event Localization and Detection Difficult? Insights from Error Analysiscited by 0
  9. 2021Spatial mixup: Directional loudness modification as data augmentation for sound event localization and detectioncited by 0
  10. 2023Feature Aggregation in Joint Sound Classification and Localization Neural Networkscited by 0
  11. 2024Audio Simulation for Sound Source Localization in Virtual Evironmentcited by 0
  12. 2025An Experimental Study on Joint Modeling for Sound Event Localization and Detection with Source Distance Estimationcited by 0
  13. 2025Acoustic Imaging for UAV Detection: Dense Beamformed Energy Maps and U-Net SELDcited by 0
  14. 2026PhysWave: Physics-Guided Latent Diffusion Models for Controllable Spatial Audio Generationcited by 0
  15. 2026RAO-Nav: Probing Omni-Language Models for Zero-shot Semantic Audio-Visual Navigationcited by 0