SCNet: Sparse Compression Network for Music Source Separation

no code implementations • 24 Jan 2024 • Weinan Tong, Jiaxu Zhu, Jun Chen, Shiyin Kang, Tao Jiang, Yang Li, Zhiyong Wu, Helen Meng

We use a higher compression ratio on subbands with less information to improve the information density and focus on modeling subbands with more information.

Music Source Separation

Text-Only Domain Adaptation for End-to-End Speech Recognition through Down-Sampling Acoustic Representation

no code implementations • 4 Sep 2023 • Jiaxu Zhu, Weinan Tong, Yaoxun Xu, Changhe Song, Zhiyong Wu, Zhao You, Dan Su, Dong Yu, Helen Meng

Mapping two modalities, speech and text, into a shared representation space, is a research topic of using text-only data to improve end-to-end automatic speech recognition (ASR) performance in new domains.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2