17 citations · 22 across the 4 of their papers we have counts for
6 papers
Improving Speech-to-Speech Translation Through Unlabeled Text
Xuan-Phi Nguyen, Sravya Popuri, Changhan Wang +3
Direct speech-to-speech translation (S2ST) is among the most challenging problems in the translation paradigm due to the significant scarcity of S2ST data. While effort has been ma…
Simple and Effective Unsupervised Speech Translation
Changhan Wang, Hirofumi Inaguma, Peng-Jen Chen +5
The amount of labeled data to train models for speech tasks is limited for most languages, however, the data scarcity is exacerbated for speech translation which requires labeled d…
Multilingual Speech Translation with Efficient Finetuning of Pretrained Models
Xian Li, Changhan Wang, Yun Tang +6
We present a simple yet effective approach to build multilingual speech-to-text (ST) translation by efficient transfer learning from pretrained speech encoder and text decoder. Our…
Zero-shot Text-to-SQL Learning with Auxiliary Task
Shuaichen Chang, Pengfei Liu, Yun Tang +3
Recent years have seen great success in the use of neural seq2seq models on the text-to-SQL task. However, little work has paid attention to how these models generalize to realisti…
I4U Submission to NIST SRE 2018: Leveraging from a Decade of Shared Experiences
Kong Aik Lee, Ville Hautamaki, Tomi Kinnunen +43
The I4U consortium was established to facilitate a joint entry to NIST speaker recognition evaluations (SRE). The latest edition of such joint submission was in SRE 2018, in which…
Towards adversarial learning of speaker-invariant representation for speech emotion recognition
Ming Tu, Yun Tang, Jing Huang +2
Speech emotion recognition (SER) has attracted great attention in recent years due to the high demand for emotionally intelligent speech interfaces. Deriving speaker-invariant repr…