Education & Resources

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 classification, speech emotion classification, and sound event detection. Recently, neural networks have been applied to tackle audio pattern recognition problems. 

In the beginning of 2020, the coronavirus disease 2019 (COVID-19) has caused a pandemic disease in over 200 countries, affecting billions of humans. Identifying and separating the infected people during the early stage is the most important step in controlling the pandemic.

The Audio Engineering Society (AES), the IEEE Consumer Technology Society (CTSoc), and the IEEE Signal Processing Society (SPS) cordially invite you to a first-of-a-kind joint event discussing the state of the art perspectives in this rapidly evolving field.

The Principal Component Analysis (PCA) is considered to be a quintessential data preprocessing tool in many machine learning applications. But the high dimensionality and massive scale of data in several of these applications means the traditional centralized PCA solutions are fast becoming irrelevant for them.