# Convolutional Recurrent Neural Networks for Polyphonic Sound Event Detection

arXiv: https://arxiv.org/abs/1702.06286 · HTML: https://mlsanity.com/paper/1702.06286/

## Key facts

- Cited by 46 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Feb 2017.

## Built on by (most cited first, 30 of 46)

- [Recurrent Variational Network: A Deep Learning Inverse Problem Solver applied to the task of Accelerated MRI Reconstruction](https://mlsanity.com/paper/2111.09639/) (2021)
- [Google Neural Network Models for Edge Devices: Analyzing and Mitigating Machine Learning Inference Bottlenecks](https://mlsanity.com/paper/2109.14320/) (2021)
- [Multi-Scale Attention for Audio Question Answering](https://mlsanity.com/paper/2305.17993/) (2023)
- [You Only Hear Once: A YOLO-like Algorithm for Audio Segmentation and Sound Event Detection](https://mlsanity.com/paper/2109.00962/) (2021)
- [Detect Any Sound: Open-Vocabulary Sound Event Detection with Multi-Modal Queries](https://mlsanity.com/paper/2507.16343/) (2025)
- [Sound Event Detection Transformer: An Event-based End-to-End Model for Sound Event Detection](https://mlsanity.com/paper/2110.02011/) (2021)
- [MAT-SED: A Masked Audio Transformer with Masked-Reconstruction Based Pre-training for Sound Event Detection](https://mlsanity.com/paper/2408.08673/) (2024)
- [Driving Style Representation in Convolutional Recurrent Neural Network Model of Driver Identification](https://mlsanity.com/paper/2102.05843/) (2021)
- [Federated Self-Supervised Learning for Acoustic Event Classification](https://mlsanity.com/paper/2203.11997/) (2022)
- [Recognizing Ornaments in Vocal Indian Art Music with Active Annotation](https://mlsanity.com/paper/2505.04419/) (2025)
- [Not in Sync: Unveiling Temporal Bias in Audio Chat Models](https://mlsanity.com/paper/2510.12185/) (2025)
- [Improving weakly supervised sound event detection with self-supervised auxiliary tasks](https://mlsanity.com/paper/2106.06858/) (2021)
- [DiffSED: Sound Event Detection with Denoising Diffusion](https://mlsanity.com/paper/2308.07293/) (2023)
- [Language-based Audio Moment Retrieval](https://mlsanity.com/paper/2409.15672/) (2024)
- [Robust detection of overlapping bioacoustic sound events](https://mlsanity.com/paper/2503.02389/) (2025)
- [DCASE 2021 Task 3: Spectrotemporally-aligned Features for Polyphonic Sound Event Localization and Detection](https://mlsanity.com/paper/2106.15190/) (2021)
- [A Comparative Study of Speaker Role Identification in Air Traffic Communication Using Deep Learning Approaches](https://mlsanity.com/paper/2111.02041/) (2021)
- [Enemy Spotted: in-game gun sound dataset for gunshot classification and localization](https://mlsanity.com/paper/2210.05917/) (2022)
- [DeFT-Mamba: Universal Multichannel Sound Separation and Polyphonic Audio Classification](https://mlsanity.com/paper/2409.12413/) (2024)
- [Prototype based Masked Audio Model for Self-Supervised Learning of Sound Event Detection](https://mlsanity.com/paper/2409.17656/) (2024)
- [Artificially Synthesising Data for Audio Classification and Segmentation to Improve Speech and Music Detection in Radio Broadcast](https://mlsanity.com/paper/2102.09959/) (2021)
- [Cross-Referencing Self-Training Network for Sound Event Detection in Audio Mixtures](https://mlsanity.com/paper/2105.13392/) (2021)
- [Dual Knowledge Distillation for Efficient Sound Event Detection](https://mlsanity.com/paper/2402.02781/) (2024)
- [MCU-Net: A Multi-prior Collaborative Deep Unfolding Network with Gates-controlled Spatial Attention for Accelerated MR Image Reconstruction](https://mlsanity.com/paper/2402.03383/) (2024)
- [From Large-scale Audio Tagging to Real-Time Explainable Emergency Vehicle Sirens Detection](https://mlsanity.com/paper/2506.23437/) (2025)
- [Semantic Audio-Visual Navigation in Continuous Environments](https://mlsanity.com/paper/2603.19660/) (2026)
- [Binaural Signal Representations for Joint Sound Event Detection and Acoustic Scene Classification](https://mlsanity.com/paper/2209.05900/) (2022)
- [Auditory Intelligence: Understanding the World Through Sound](https://mlsanity.com/paper/2508.07829/) (2025)
- [Audio Attacks and Defenses against AED Systems -- A Practical Study](https://mlsanity.com/paper/2106.07428/) (2021)
- [Improving Polyphonic Sound Event Detection on Multichannel Recordings with the Sorensen-Dice Coefficient Loss and Transfer Learning](https://mlsanity.com/paper/2107.10471/) (2021)

## Abstract (arXiv)

Sound events often occur in unstructured environments where they exhibit wide variations in their frequency content and temporal structure. Convolutional neural networks (CNN) are able to extract higher level features that are invariant to local spectral and temporal variations. Recurrent neural networks (RNNs) are powerful in learning the longer term temporal context in the audio signals. CNNs and RNNs as classifiers have recently shown improved performances over established methods in various sound recognition tasks. We combine these two approaches in a Convolutional Recurrent Neural Network (CRNN) and apply it on a polyphonic sound event detection task. We compare the performance of the proposed CRNN method with CNN, RNN, and other established methods, and observe a considerable improvement for four different datasets consisting of everyday sound events.