Significance of Speaker Embeddings and Temporal Context for Depression Detection

Understand

Depression detection from speech has attracted a lot of attention in recent years.

• However, the significance of speaker-specific information in depression detection has not yet been explored.
• In this work, we analyze the significance of speaker embeddings for the task of depression detection from speech.
• Experimental results show that the speaker embeddings provide important cues to achieve state-of-the-art performance in depression detection.