Search Results for author: Yun Tang

Found 30 papers, 5 papers with code

Hybrid Transducer and Attention based Encoder-Decoder Modeling for Speech-to-Text Tasks

no code implementations4 May 2023 Yun Tang, Anna Y. Sun, Hirofumi Inaguma, Xinyue Chen, Ning Dong, Xutai Ma, Paden D. Tomasello, Juan Pino

In order to leverage strengths of both modeling methods, we propose a solution by combining Transducer and Attention based Encoder-Decoder (TAED) for speech-to-text tasks.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +4

Enhancing Speech-to-Speech Translation with Multiple TTS Targets

no code implementations10 Apr 2023 Jiatong Shi, Yun Tang, Ann Lee, Hirofumi Inaguma, Changhan Wang, Juan Pino, Shinji Watanabe

It has been known that direct speech-to-speech translation (S2ST) models usually suffer from the data scarcity issue because of the limited existing parallel materials for both source and target speech.

Speech-to-Speech Translation Speech-to-Text Translation +1

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

1 code implementation15 Dec 2022 Hirofumi Inaguma, Sravya Popuri, Ilia Kulikov, Peng-Jen Chen, Changhan Wang, Yu-An Chung, Yun Tang, Ann Lee, Shinji Watanabe, Juan Pino

We enhance the model performance by subword prediction in the first-pass decoder, advanced two-pass decoder architecture design and search strategy, and better training regularization.

Denoising Speech-to-Speech Translation +3

Improving Speech-to-Speech Translation Through Unlabeled Text

no code implementations26 Oct 2022 Xuan-Phi Nguyen, Sravya Popuri, Changhan Wang, Yun Tang, Ilia Kulikov, Hongyu Gong

Direct speech-to-speech translation (S2ST) is among the most challenging problems in the translation paradigm due to the significant scarcity of S2ST data.

Machine Translation speech-recognition +3

Simple and Effective Unsupervised Speech Translation

no code implementations18 Oct 2022 Changhan Wang, Hirofumi Inaguma, Peng-Jen Chen, Ilia Kulikov, Yun Tang, Wei-Ning Hsu, Michael Auli, Juan Pino

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 data covering two different languages.

Machine Translation speech-recognition +6

A Survey on Scenario-Based Testing for Automated Driving Systems in High-Fidelity Simulation

no code implementations2 Dec 2021 Ziyuan Zhong, Yun Tang, Yuan Zhou, Vania de Oliveira Neves, Yang Liu, Baishakhi Ray

To bridge this gap, in this work, we provide a generic formulation of scenario-based testing in high-fidelity simulation and conduct a literature review on the existing works.

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

no code implementations15 Oct 2021 Xutai Ma, Hongyu Gong, Danni Liu, Ann Lee, Yun Tang, Peng-Jen Chen, Wei-Ning Hsu, Phillip Koehn, Juan Pino

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

Speech Synthesis Speech-to-Speech Translation +1

Contrastive Clustering to Mine Pseudo Parallel Data for Unsupervised Translation

no code implementations ICLR 2022 Xuan-Phi Nguyen, Hongyu Gong, Yun Tang, Changhan Wang, Philipp Koehn, Shafiq Joty

Modern unsupervised machine translation systems mostly train their models by generating synthetic parallel training data from large unlabeled monolingual corpora of different languages through various means, such as iterative back-translation.

Clustering Translation +1

Multilingual Speech Translation from Efficient Finetuning of Pretrained Models

no code implementations ACL 2021 Xian Li, Changhan Wang, Yun Tang, Chau Tran, Yuqing Tang, Juan Pino, Alexei Baevski, Alexis Conneau, Michael Auli

We present a simple yet effective approach to build multilingual speech-to-text (ST) translation through efficient transfer learning from a pretrained speech encoder and text decoder.

Text Generation Transfer Learning +1

FST: the FAIR Speech Translation System for the IWSLT21 Multilingual Shared Task

no code implementations ACL (IWSLT) 2021 Yun Tang, Hongyu Gong, Xian Li, Changhan Wang, Juan Pino, Holger Schwenk, Naman Goyal

In this paper, we describe our end-to-end multilingual speech translation system submitted to the IWSLT 2021 evaluation campaign on the Multilingual Speech Translation shared task.

Transfer Learning Translation

Direct speech-to-speech translation with discrete units

no code implementations ACL 2022 Ann Lee, Peng-Jen Chen, Changhan Wang, Jiatao Gu, Sravya Popuri, Xutai Ma, Adam Polyak, Yossi Adi, Qing He, Yun Tang, Juan Pino, Wei-Ning Hsu

When target text transcripts are available, we design a joint speech and text training framework that enables the model to generate dual modality output (speech and text) simultaneously in the same inference pass.

Speech-to-Speech Translation Text Generation +1

Pay Better Attention to Attention: Head Selection in Multilingual and Multi-Domain Sequence Modeling

no code implementations NeurIPS 2021 Hongyu Gong, Yun Tang, Juan Pino, Xian Li

We further propose attention sharing strategies to facilitate parameter sharing and specialization in multilingual and multi-domain sequence modeling.

speech-recognition Speech Recognition +2

Multilingual Speech Translation with Efficient Finetuning of Pretrained Models

no code implementations24 Oct 2020 Xian Li, Changhan Wang, Yun Tang, Chau Tran, Yuqing Tang, Juan Pino, Alexei Baevski, Alexis Conneau, Michael Auli

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.

Cross-Lingual Transfer Text Generation +2

A General Multi-Task Learning Framework to Leverage Text Data for Speech to Text Tasks

no code implementations21 Oct 2020 Yun Tang, Juan Pino, Changhan Wang, Xutai Ma, Dmitriy Genzel

We demonstrate that representing text input as phoneme sequences can reduce the difference between speech and text inputs, and enhance the knowledge transfer from text corpora to the speech to text tasks.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +5

Orthogonal Relation Transforms with Graph Context Modeling for Knowledge Graph Embedding

no code implementations ACL 2020 Yun Tang, Jing Huang, Guangtao Wang, Xiaodong He, Bo-Wen Zhou

Translational distance-based knowledge graph embedding has shown progressive improvements on the link prediction task, from TransE to the latest state-of-the-art RotatE.

Knowledge Graph Embedding Link Prediction

Relation Module for Non-answerable Prediction on Question Answering

no code implementations23 Oct 2019 Kevin Huang, Yun Tang, Jing Huang, Xiaodong He, Bo-Wen Zhou

In this paper, we aim to improve a MRC model's ability to determine whether a question has an answer in a given context (e. g. the recently proposed SQuAD 2. 0 task).

Machine Reading Comprehension Question Answering +1

Zero-shot Text-to-SQL Learning with Auxiliary Task

1 code implementation29 Aug 2019 Shuaichen Chang, PengFei Liu, Yun Tang, Jing Huang, Xiaodong He, Bo-Wen Zhou

Recent years have seen great success in the use of neural seq2seq models on the text-to-SQL task.


End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion

1 code implementation11 Nov 2018 Chao Shang, Yun Tang, Jing Huang, Jinbo Bi, Xiaodong He, Bo-Wen Zhou

The recent graph convolutional network (GCN) provides another way of learning graph node embedding by successfully utilizing graph connectivity structure.

Knowledge Base Completion Knowledge Graph Embedding +2

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