activity
20192023
most citedMultilingual Speech Translation with Efficient Finetuning of Pretrained Models

27 citations · 64 across the 12 of their papers we have counts for

collaborators

12 papers

cs.SD2023★ 1 cited

Exploration on HuBERT with Multiple Resolutions

Jiatong Shi, Yun Tang, Hirofumi Inaguma +3

Hidden-unit BERT (HuBERT) is a widely-used self-supervised learning (SSL) model in speech processing. However, we argue that its fixed 20ms resolution for hidden representations wo…

cs.SD2023

ESPnet-ST-v2: Multipurpose Spoken Language Translation Toolkit

Brian Yan, Jiatong Shi, Yun Tang +13

ESPnet-ST-v2 is a revamp of the open-source ESPnet-ST toolkit necessitated by the broadening interests of the spoken language translation community. ESPnet-ST-v2 supports 1) offlin…

cs.CL2022★ 3 cited

UnitY: Two-pass Direct Speech-to-speech Translation with Discrete Units

Hirofumi Inaguma, Sravya Popuri, Ilia Kulikov +7

Direct speech-to-speech translation (S2ST), in which all components can be optimized jointly, is advantageous over cascaded approaches to achieve fast inference with a simplified p…

cs.CL2022

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…

cs.CL2022★ 2 cited

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…

cs.CL2021★ 1 cited

Direct Simultaneous Speech-to-Speech Translation with Variational Monotonic Multihead Attention

Xutai Ma, Hongyu Gong, Danni Liu +6

We present a direct simultaneous speech-to-speech translation (Simul-S2ST) model, Furthermore, the generation of translation is independent from intermediate text representations.…

cs.CL2021

From Start to Finish: Latency Reduction Strategies for Incremental Speech Synthesis in Simultaneous Speech-to-Speech Translation

Danni Liu, Changhan Wang, Hongyu Gong +3

Speech-to-speech translation (S2ST) converts input speech to speech in another language. A challenge of delivering S2ST in real time is the accumulated delay between the translatio…

cs.CL2021★ 7 cited

Direct speech-to-speech translation with discrete units

Ann Lee, Peng-Jen Chen, Changhan Wang +9

We present a direct speech-to-speech translation (S2ST) model that translates speech from one language to speech in another language without relying on intermediate text generation…

cs.CL2020★ 27 cited

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…

cs.CL2019★ 3 cited

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…

eess.AS2019★ 3 cited

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…

eess.AS2019★ 17 cited

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…