36 citations · 69 across the 6 of their papers we have counts for
11 papers · 1 filter
Enhancing Audio Augmentation Methods with Consistency Learning
Turab Iqbal, Karim Helwani, Arvindh Krishnaswamy +1
Data augmentation is an inexpensive way to increase training data diversity and is commonly achieved via transformations of existing data. For tasks such as classification, there i…
An Improved Event-Independent Network for Polyphonic Sound Event Localization and Detection
Yin Cao, Turab Iqbal, Qiuqiang Kong +3
Polyphonic sound event localization and detection (SELD), which jointly performs sound event detection (SED) and direction-of-arrival (DoA) estimation, detects the type and occurre…
Learning with Out-of-Distribution Data for Audio Classification
Turab Iqbal, Yin Cao, Qiuqiang Kong +2
In supervised machine learning, the assumption that training data is labelled correctly is not always satisfied. In this paper, we investigate an instance of labelling error for cl…
PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition
Qiuqiang Kong, Yin Cao, Turab Iqbal +3
Audio pattern recognition is an important research topic in the machine learning area, and includes several tasks such as audio tagging, acoustic scene classification, music classi…
Polyphonic Sound Event Detection and Localization using a Two-Stage Strategy
Yin Cao, Qiuqiang Kong, Turab Iqbal +3
Sound event detection (SED) and localization refer to recognizing sound events and estimating their spatial and temporal locations. Using neural networks has become the prevailing…
Cross-task learning for audio tagging, sound event detection spatial localization: DCASE 2019 baseline systems
Qiuqiang Kong, Yin Cao, Turab Iqbal +3
The Detection and Classification of Acoustic Scenes and Events (DCASE) 2019 challenge focuses on audio tagging, sound event detection and spatial localisation. DCASE 2019 consists…