Speaker Recognition Task
Speaker recognition, the task of identifying individuals based on their voice, aims to develop robust and accurate systems for various applications. Current research focuses on improving robustness to noisy environments and channel variations, often employing deep learning architectures like TDNNs and Transformers, sometimes enhanced with attention mechanisms and self-supervised learning techniques such as wav2vec 2.0. These advancements are driven by the need for reliable speaker verification in diverse real-world scenarios, impacting fields ranging from security and forensics to personalized user interfaces and accessibility technologies.
Papers
Karaoker: Alignment-free singing voice synthesis with speech training data
Panos Kakoulidis, Nikolaos Ellinas, Georgios Vamvoukakis, Konstantinos Markopoulos, June Sig Sung, Gunu Jho, Pirros Tsiakoulis, Aimilios Chalamandaris
Reliable Visualization for Deep Speaker Recognition
Pengqi Li, Lantian Li, Askar Hamdulla, Dong Wang