activity
20172025
most citedPSLA: Improving Audio Tagging with Pretraining, Sampling, Labeling, and Aggregation

164 citations · 797 across the 24 of their papers we have counts for

collaborators

25 papers

cs.LG2025

Can Diffusion Models Disentangle? A Theoretical Perspective

Liming Wang, Muhammad Jehanzeb Mirza, Yishu Gong +6

This paper presents a novel theoretical framework for understanding how diffusion models can learn disentangled representations. Within this framework, we establish identifiability…

eess.AS2024

DASS: Distilled Audio State Space Models Are Stronger and More Duration-Scalable Learners

Saurabhchand Bhati, Yuan Gong, Leonid Karlinsky +3

State-space models (SSMs) have emerged as an alternative to Transformers for audio modeling due to their high computational efficiency with long inputs. While recent efforts on Aud…

cs.SD2024

Automatic Prediction of Amyotrophic Lateral Sclerosis Progression using Longitudinal Speech Transformer

Liming Wang, Yuan Gong, Nauman Dawalatabad +7

Automatic prediction of amyotrophic lateral sclerosis (ALS) disease progression provides a more efficient and objective alternative than manual approaches. We propose ALS longitudi…

eess.AS2024

Whisper-Flamingo: Integrating Visual Features into Whisper for Audio-Visual Speech Recognition and Translation

Andrew Rouditchenko, Yuan Gong, Samuel Thomas +4

Audio-Visual Speech Recognition (AVSR) uses lip-based video to improve performance in noise. Since videos are harder to obtain than audio, the video training data of AVSR models is…

cs.SD2023

Joint Audio and Speech Understanding

Yuan Gong, Alexander H. Liu, Hongyin Luo +2

Humans are surrounded by audio signals that include both speech and non-speech sounds. The recognition and understanding of speech and non-speech audio events, along with a profoun…

cs.CL2023

Natural Language Embedded Programs for Hybrid Language Symbolic Reasoning

Tianhua Zhang, Jiaxin Ge, Hongyin Luo +7

How can we perform computations over natural language representations to solve tasks that require symbolic and numeric reasoning? We propose natural language embedded programs (NLE…

cs.SD2023★ 61 cited

Whisper-AT: Noise-Robust Automatic Speech Recognizers are Also Strong General Audio Event Taggers

Yuan Gong, Sameer Khurana, Leonid Karlinsky +1

In this paper, we focus on Whisper, a recent automatic speech recognition model trained with a massive 680k hour labeled speech corpus recorded in diverse conditions. We first show…

cs.CL2023★ 6 cited

SAIL: Search-Augmented Instruction Learning

Hongyin Luo, Yung-Sung Chuang, Yuan Gong +6

Large language models (LLMs) have been significantly improved by instruction fine-tuning, but still lack transparency and the ability to utilize up-to-date knowledge and informatio…

eess.AS2023★ 18 cited

Listen, Think, and Understand

Yuan Gong, Hongyin Luo, Alexander H. Liu +2

The ability of artificial intelligence (AI) systems to perceive and comprehend audio signals is crucial for many applications. Although significant progress has been made in this a…

cs.MM2022★ 17 cited

Contrastive Audio-Visual Masked Autoencoder

Yuan Gong, Andrew Rouditchenko, Alexander H. Liu +4

In this paper, we first extend the recent Masked Auto-Encoder (MAE) model from a single modality to audio-visual multi-modalities. Subsequently, we propose the Contrastive Audio-Vi…

cs.CV2022★ 23 cited

UAVM: Towards Unifying Audio and Visual Models

Yuan Gong, Alexander H. Liu, Andrew Rouditchenko +1

Conventional audio-visual models have independent audio and video branches. In this work, we unify the audio and visual branches by designing a Unified Audio-Visual Model (UAVM). T…

cs.SD2022★ 43 cited

Vocalsound: A Dataset for Improving Human Vocal Sounds Recognition

Yuan Gong, Jin Yu, James Glass

Recognizing human non-speech vocalizations is an important task and has broad applications such as automatic sound transcription and health condition monitoring. However, existing…

cs.SD2022★ 48 cited

Transformer-Based Multi-Aspect Multi-Granularity Non-Native English Speaker Pronunciation Assessment

Yuan Gong, Ziyi Chen, Iek-Heng Chu +2

Automatic pronunciation assessment is an important technology to help self-directed language learners. While pronunciation quality has multiple aspects including accuracy, fluency,…

cs.SD2022★ 17 cited

CMKD: CNN/Transformer-Based Cross-Model Knowledge Distillation for Audio Classification

Yuan Gong, Sameer Khurana, Andrew Rouditchenko +1

Audio classification is an active research area with a wide range of applications. Over the past decade, convolutional neural networks (CNNs) have been the de-facto standard buildi…

cs.SD2021★ 3 cited

SSAST: Self-Supervised Audio Spectrogram Transformer

Yuan Gong, Cheng-I Jeff Lai, Yu-An Chung +1

Recently, neural networks based purely on self-attention, such as the Vision Transformer (ViT), have been shown to outperform deep learning models constructed with convolutional ne…

cs.SD2021★ 37 cited

AST: Audio Spectrogram Transformer

Yuan Gong, Yu-An Chung, James Glass

In the past decade, convolutional neural networks (CNNs) have been widely adopted as the main building block for end-to-end audio classification models, which aim to learn a direct…

cs.SD2021★ 164 cited

PSLA: Improving Audio Tagging with Pretraining, Sampling, Labeling, and Aggregation

Yuan Gong, Yu-An Chung, James Glass

Audio tagging is an active research area and has a wide range of applications. Since the release of AudioSet, great progress has been made in advancing model performance, which mos…

cs.SD2020★ 34 cited

Detecting Replay Attacks Using Multi-Channel Audio: A Neural Network-Based Method

Yuan Gong, Jian Yang, Christian Poellabauer

With the rapidly growing number of security-sensitive systems that use voice as the primary input, it becomes increasingly important to address these systems' potential vulnerabili…

cs.CV2019★ 106 cited

Second-order Non-local Attention Networks for Person Re-identification

Bryan, Xia, Yuan Gong +2

Recent efforts have shown promising results for person re-identification by designing part-based architectures to allow a neural network to learn discriminative representations fro…

cs.CR2019★ 8 cited

Real-Time Adversarial Attacks

Yuan Gong, Boyang Li, Christian Poellabauer +1

In recent years, many efforts have demonstrated that modern machine learning algorithms are vulnerable to adversarial attacks, where small, but carefully crafted, perturbations on…

cs.CR2019★ 2 cited

ReMASC: Realistic Replay Attack Corpus for Voice Controlled Systems

Yuan Gong, Jian Yang, Jacob Huber +2

This paper introduces a new database of voice recordings with the goal of supporting research on vulnerabilities and protection of voice-controlled systems (VCSs). In contrast to p…

cs.CR2018★ 32 cited

Protecting Voice Controlled Systems Using Sound Source Identification Based on Acoustic Cues

Yuan Gong, Christian Poellabauer

Over the last few years, a rapidly increasing number of Internet-of-Things (IoT) systems that adopt voice as the primary user input have emerged. These systems have been shown to b…

cs.CL2018★ 151 cited

Topic Modeling Based Multi-modal Depression Detection

Yuan Gong, Christian Poellabauer

Major depressive disorder is a common mental disorder that affects almost 7% of the adult U.S. population. The 2017 Audio/Visual Emotion Challenge (AVEC) asks participants to build…

cs.CR2018★ 27 cited

An Overview of Vulnerabilities of Voice Controlled Systems

Yuan Gong, Christian Poellabauer

Over the last few years, a rapidly increasing number of Internet-of-Things (IoT) systems that adopt voice as the primary user input have emerged. These systems have been shown to b…