2 citations · 3 across the 7 of their papers we have counts for
7 papers
CONVERSER: Few-Shot Conversational Dense Retrieval with Synthetic Data Generation
Chao-Wei Huang, Chen-Yu Hsu, Tsu-Yuan Hsu +2
Conversational search provides a natural interface for information retrieval (IR). Recent approaches have demonstrated promising results in applying dense retrieval to conversation…
Towards General-Purpose Text-Instruction-Guided Voice Conversion
Chun-Yi Kuan, Chen An Li, Tsu-Yuan Hsu +5
This paper introduces a novel voice conversion (VC) model, guided by text instructions such as "articulate slowly with a deep tone" or "speak in a cheerful boyish voice". Unlike tr…
Improving Cascaded Unsupervised Speech Translation with Denoising Back-translation
Yu-Kuan Fu, Liang-Hsuan Tseng, Jiatong Shi +4
Most of the speech translation models heavily rely on parallel data, which is hard to collect especially for low-resource languages. To tackle this issue, we propose to build a cas…
Ensemble knowledge distillation of self-supervised speech models
Kuan-Po Huang, Tzu-hsun Feng, Yu-Kuan Fu +5
Distilled self-supervised models have shown competitive performance and efficiency in recent years. However, there is a lack of experience in jointly distilling multiple self-super…
Model Extraction Attack against Self-supervised Speech Models
Tsu-Yuan Hsu, Chen-An Li, Tung-Yu Wu +1
Self-supervised learning (SSL) speech models generate meaningful representations of given clips and achieve incredible performance across various downstream tasks. Model extraction…
Improving generalizability of distilled self-supervised speech processing models under distorted settings
Kuan-Po Huang, Yu-Kuan Fu, Tsu-Yuan Hsu +5
Self-supervised learned (SSL) speech pre-trained models perform well across various speech processing tasks. Distilled versions of SSL models have been developed to match the needs…
The Efficacy of Self-Supervised Speech Models for Audio Representations
Tung-Yu Wu, Chen-An Li, Tzu-Han Lin +2
Self-supervised learning (SSL) speech models, which can serve as powerful upstream models to extract meaningful speech representations, have achieved unprecedented success in speec…