Target Speaker Voice Activity Detection

Target speaker voice activity detection (TS-VAD) aims to identify when a specific speaker is active in a multi-speaker audio recording, a crucial step in speaker diarization and speech processing. Recent research emphasizes improving TS-VAD accuracy using neural network architectures, particularly sequence-to-sequence models, transformers, and generative models like flow-matching, often incorporating speaker embeddings and attention mechanisms to handle complex scenarios like overlapping speech and noisy environments. These advancements are driving improvements in meeting transcription, personalized diarization, and other applications requiring accurate speaker identification in challenging acoustic conditions. The resulting improvements in accuracy and robustness are significant for advancing both the field of speech processing and real-world applications.