3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CL2022
Once-for-All Sequence Compression for Self-Supervised Speech Models
Hsuan-Jui Chen, Yen Meng, Hung-yi Lee
The sequence length along the time axis is often the dominant factor of the computation in speech processing. Works have been proposed to reduce the sequence length for lowering th…
cs.CL2022
On Compressing Sequences for Self-Supervised Speech Models
Yen Meng, Hsuan-Jui Chen, Jiatong Shi +4
Compressing self-supervised models has become increasingly necessary, as self-supervised models become larger. While previous approaches have primarily focused on compressing the m…
eess.AS2021★ 3 cited
Don't speak too fast: The impact of data bias on self-supervised speech models
Yen Meng, Yi-Hui Chou, Andy T. Liu +1
Self-supervised Speech Models (S3Ms) have been proven successful in many speech downstream tasks, like ASR. However, how pre-training data affects S3Ms' downstream behavior remains…