Shot Speaker

Shot speaker adaptation in text-to-speech (TTS) and speaker identification focuses on generating or recognizing speech from limited speaker data. Current research emphasizes efficient few-shot methods, employing lightweight modules like residual adapters within neural networks to minimize computational costs and prevent overfitting while maintaining high speech quality and speaker similarity. These advancements are crucial for scaling personalized TTS systems to numerous speakers and improving the accuracy of speaker identification in scenarios with limited training examples. The resulting technologies have significant implications for applications such as personalized voice assistants, accessible education through multilingual lecture generation, and improved forensic speaker analysis.