# Sound Event Detection Using Spatial Features and Convolutional Recurrent Neural Network

arXiv: https://arxiv.org/abs/1706.02291 · HTML: https://mlsanity.com/paper/1706.02291/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Jun 2017.

## Built on by (most cited first, 14 of 14)

- [L3DAS22 Challenge: Learning 3D Audio Sources in a Real Office Environment](https://mlsanity.com/paper/2202.10372/) (2022)
- [L3DAS21 Challenge: Machine Learning for 3D Audio Signal Processing](https://mlsanity.com/paper/2104.05499/) (2021)
- [Sound Event Detection Transformer: An Event-based End-to-End Model for Sound Event Detection](https://mlsanity.com/paper/2110.02011/) (2021)
- [Binaural Signal Representations for Joint Sound Event Detection and Acoustic Scene Classification](https://mlsanity.com/paper/2209.05900/) (2022)
- [Spatial and Semantic Embedding Integration for Stereo Sound Event Localization and Detection in Regular Videos](https://mlsanity.com/paper/2507.04845/) (2025)
- [Integrating Spatial and Semantic Embeddings for Stereo Sound Event Localization in Videos](https://mlsanity.com/paper/2509.06598/) (2025)
- [Improving Polyphonic Sound Event Detection on Multichannel Recordings with the Sorensen-Dice Coefficient Loss and Transfer Learning](https://mlsanity.com/paper/2107.10471/) (2021)
- [Past and Future Motion Guided Network for Audio Visual Event Localization](https://mlsanity.com/paper/2205.03802/) (2022)
- [Improving Primate Sounds Classification using Binary Presorting for Deep Learning](https://mlsanity.com/paper/2306.16054/) (2023)
- [Feature Aggregation in Joint Sound Classification and Localization Neural Networks](https://mlsanity.com/paper/2310.19063/) (2023)
- [SoundLoc3D: Invisible 3D Sound Source Localization and Classification Using a Multimodal RGB-D Acoustic Camera](https://mlsanity.com/paper/2412.16861/) (2024)
- [Phase-Aware Deep Learning with Complex-Valued CNNs for Audio Signal Applications](https://mlsanity.com/paper/2510.09926/) (2025)
- [ToS: A Team of Specialists ensemble framework for Stereo Sound Event Localization and Detection with distance estimation in Video](https://mlsanity.com/paper/2601.17611/) (2026)
- [Towards Open World Sound Event Detection](https://mlsanity.com/paper/2605.03934/) (2026)

## Abstract (arXiv)

This paper proposes to use low-level spatial features extracted from multichannel audio for sound event detection. We extend the convolutional recurrent neural network to handle more than one type of these multichannel features by learning from each of them separately in the initial stages. We show that instead of concatenating the features of each channel into a single feature vector the network learns sound events in multichannel audio better when they are presented as separate layers of a volume. Using the proposed spatial features over monaural features on the same network gives an absolute F-score improvement of 6.1% on the publicly available TUT-SED 2016 dataset and 2.7% on the TUT-SED 2009 dataset that is fifteen times larger.