Deepfake Speech Detection

Deepfake speech detection aims to identify artificially generated audio, combating the spread of manipulated voice recordings. Current research focuses on improving the generalization of detection models across diverse datasets and deepfake generation techniques, exploring architectures like Mixture of Experts and leveraging pre-trained models such as WavLM for feature extraction, often incorporating data augmentation strategies. This field is crucial for safeguarding against malicious uses of synthesized speech, impacting areas like security, law enforcement, and the authenticity of digital media.