Auditory Verbal Hallucination

Auditory verbal hallucinations (AVHs), the perception of voices or sounds not present in reality, are a significant focus of research, particularly concerning their assessment and prediction in mental health contexts. Current research employs machine learning models, including neural networks and generative adversarial networks (GANs), to analyze both self-reported data (e.g., valence of voices) and passively collected mobile sensor data to improve the prediction and understanding of AVHs. These efforts aim to develop more accurate diagnostic tools and potentially personalized interventions for individuals experiencing AVHs, improving mental health care. Furthermore, related research explores "hallucinations" in large language models, highlighting the need for robust methods to distinguish between genuine and generated audio information.