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eess.AS2023
AutoPrep: An Automatic Preprocessing Framework for In-the-Wild Speech Data
Jianwei Yu, Hangting Chen, Yanyao Bian +6
Recently, the utilization of extensive open-sourced text data has significantly advanced the performance of text-based large language models (LLMs). However, the use of in-the-wild…
eess.AS2022
Speaker-Aware Mixture of Mixtures Training for Weakly Supervised Speaker Extraction
Zifeng Zhao, Rongzhi Gu, Dongchao Yang +2
Dominant researches adopt supervised training for speaker extraction, while the scarcity of ideally clean corpus and channel mismatch problem are rarely considered. To this end, we…