b'Shang-Wen Li'

research

∙ 09/19/2023

AV-SUPERB: A Multi-Task Evaluation Benchmark for Audio-Visual Representation Models

Audio-visual representation learning aims to develop systems with human-...

0 Yuan Tseng, et al. ∙

research

∙ 05/29/2023

Improving Textless Spoken Language Understanding with Discrete Units as Intermediate Target

Spoken Language Understanding (SLU) is a task that aims to extract seman...

0 Guan-Wei Wu, et al. ∙

research

∙ 05/26/2023

Expand, Rerank, and Retrieve: Query Reranking for Open-Domain Question Answering

We propose EAR, a query Expansion And Reranking approach for improving p...

0 Yung-Sung Chuang, et al. ∙

research

∙ 05/19/2023

Syllable Discovery and Cross-Lingual Generalization in a Visually Grounded, Self-Supervised Speech Mode

In this paper, we show that representations capturing syllabic units eme...

0 Puyuan Peng, et al. ∙

research

∙ 05/18/2023

ML-SUPERB: Multilingual Speech Universal PERformance Benchmark

Speech processing Universal PERformance Benchmark (SUPERB) is a leaderbo...

0 Jiatong Shi, et al. ∙

research

∙ 04/14/2023

DINOv2: Learning Robust Visual Features without Supervision

The recent breakthroughs in natural language processing for model pretra...

1 Maxime Oquab, et al. ∙

research

∙ 03/01/2023

SpeechPrompt v2: Prompt Tuning for Speech Classification Tasks

Prompt tuning is a technology that tunes a small set of parameters to st...

0 Kai-Wei Chang, et al. ∙

research

∙ 12/15/2022

MAViL: Masked Audio-Video Learners

We present Masked Audio-Video Learners (MAViL) to train audio-visual rep...

0 Po-Yao Huang, et al. ∙

research

∙ 11/15/2022

Introducing Semantics into Speech Encoders

Recent studies find existing self-supervised speech encoders contain pri...

10 Derek Xu, et al. ∙

research

∙ 10/16/2022

SUPERB @ SLT 2022: Challenge on Generalization and Efficiency of Self-Supervised Speech Representation Learning

We present the SUPERB challenge at SLT 2022, which aims at learning self...

0 Tzu-hsun Feng, et al. ∙

research

∙ 10/10/2022

Exploring Efficient-tuning Methods in Self-supervised Speech Models

In this study, we aim to explore efficient tuning methods for speech sel...

0 Zih-Ching Chen, et al. ∙

research

∙ 05/21/2022

Self-Supervised Speech Representation Learning: A Review

Although supervised deep learning has revolutionized speech and audio pr...

0 Abdelrahman Mohamed, et al. ∙

research

∙ 05/03/2022

Meta Learning for Natural Language Processing: A Survey

Deep learning has been the mainstream technique in natural language proc...

0 Hung-Yi Lee, et al. ∙

research

∙ 03/31/2022

An Exploration of Prompt Tuning on Generative Spoken Language Model for Speech Processing Tasks

Speech representations learned from Self-supervised learning (SSL) model...

0 Kai-Wei Chang, et al. ∙

research

∙ 03/27/2022

Listen, Adapt, Better WER: Source-free Single-utterance Test-time Adaptation for Automatic Speech Recognition

Although deep learning-based end-to-end Automatic Speech Recognition (AS...

0 Guan-Ting Lin, et al. ∙

research

∙ 03/14/2022

SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities

Transfer learning has proven to be crucial in advancing the state of spe...

0 Hsiang-Sheng Tsai, et al. ∙

research

∙ 03/09/2022

DUAL: Discrete Spoken Unit Adaptive Learning for Textless Spoken Question Answering

Spoken Question Answering (SQA) is to find the answer from a spoken docu...

0 Guan-Ting Lin, et al. ∙

research

∙ 10/16/2021

Lifelong Pretraining: Continually Adapting Language Models to Emerging Corpora

Pretrained language models (PTLMs) are typically learned over a large, s...

0 Xisen Jin, et al. ∙

research

∙ 09/12/2021

Pairwise Supervised Contrastive Learning of Sentence Representations

Many recent successes in sentence representation learning have been achi...

0 Dejiao Zhang, et al. ∙

research

∙ 06/14/2021

Mitigating Biases in Toxic Language Detection through Invariant Rationalization

Automatic detection of toxic language plays an essential role in protect...

0 Yung-Sung Chuang, et al. ∙

research

∙ 06/06/2021

Meta-learning for downstream aware and agnostic pretraining

Neural network pretraining is gaining attention due to its outstanding p...

0 Hongyin Luo, et al. ∙

research

∙ 05/03/2021

SUPERB: Speech processing Universal PERformance Benchmark

Self-supervised learning (SSL) has proven vital for advancing research i...

0 Shu-wen Yang, et al. ∙

research

∙ 03/12/2021

Cooperative Learning of Zero-Shot Machine Reading Comprehension

Pretrained language models have significantly improved the performance o...

0 Hongyin Luo, et al. ∙

research

∙ 01/24/2021

Knowledge Grounded Conversational Symptom Detection with Graph Memory Networks

In this work, we propose a novel goal-oriented dialog task, automatic sy...

0 Hongyin Luo, et al. ∙

research

∙ 01/20/2021

Zero-shot Generalization in Dialog State Tracking through Generative Question Answering

Dialog State Tracking (DST), an integral part of modern dialog systems, ...

5 Shuyang Li, et al. ∙

research

∙ 12/31/2020

Educational Content Linking for Enhancing Learning Need Remediation in MOOCs

Since its introduction in 2011, there have been over 4000 MOOCs on vario...

0 Shang-Wen Li, et al. ∙

research

∙ 11/30/2020

Meta learning to classify intent and slot labels with noisy few shot examples

Recently deep learning has dominated many machine learning areas, includ...

0 Shang-Wen Li, et al. ∙

research

∙ 11/11/2020

Towards Semi-Supervised Semantics Understanding from Speech

Much recent work on Spoken Language Understanding (SLU) falls short in a...

10 Cheng-I Lai, et al. ∙

research

∙ 10/26/2020

Semi-Supervised Spoken Language Understanding via Self-Supervised Speech and Language Model Pretraining

Much recent work on Spoken Language Understanding (SLU) is limited in at...

0 Cheng-I Lai, et al. ∙

research

∙ 10/09/2020

Style Attuned Pre-training and Parameter Efficient Fine-tuning for Spoken Language Understanding

Neural models have yielded state-of-the-art results in deciphering spoke...

9 Jin Cao, et al. ∙

research

∙ 07/12/2020

TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech

We introduce a self-supervised speech pre-training method called TERA, w...

0 Andy T. Liu, et al. ∙

research

∙ 05/19/2020

Prototypical Q Networks for Automatic Conversational Diagnosis and Few-Shot New Disease Adaption

Spoken dialog systems have seen applications in many domains, including ...

0 Hongyin Luo, et al. ∙

research

∙ 05/18/2020

Audio ALBERT: A Lite BERT for Self-supervised Learning of Audio Representation

For self-supervised speech processing, it is crucial to use pretrained m...

0 Po-Han Chi, et al. ∙

research

∙ 12/11/2017

Learning Robust Dialog Policies in Noisy Environments

Modern virtual personal assistants provide a convenient interface for co...

0 Maryam Fazel-Zarandi, et al. ∙

Shang-Wen Li

Featured Co-authors