Speaker Change Detection

Speaker change detection (SCD) aims to automatically identify points in an audio recording where one speaker's voice is replaced by another's, a crucial step in applications like meeting transcription and diarization. Current research emphasizes improving SCD accuracy using various deep learning architectures, including transformer-based models and those leveraging self-supervised learning features from pre-trained speech recognition models, often incorporating multimodal information (audio and text) for enhanced performance. These advancements are driving improvements in the efficiency and accuracy of speech processing systems, with significant implications for applications requiring real-time speaker identification and transcription in diverse settings.