An End-to-End Audio Classification System based on Raw Waveforms and Mix-Training Strategy

Understand

Audio classification can distinguish different kinds of sounds, which is helpful for intelligent applications in daily life.

• However, it remains a challenging task since the sound events in an audio clip is probably multiple, even overlapping.
• This paper introduces an end-to-end audio classification system based on raw waveforms and mix-training strategy.
• Compared to human-designed features which have been widely used in existing research, raw waveforms contain more complete information and are more appropriate for multi-label classification.