activity
20162024
most citedSeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging

632 citations · 2k across the 38 of their papers we have counts for

collaborators

44 papers

eess.AS2024

Mind the Domain Gap: a Systematic Analysis on Bioacoustic Sound Event Detection

Jinhua Liang, Ines Nolasco, Burooj Ghani +3

Detecting the presence of animal vocalisations in nature is essential to study animal populations and their behaviors. A recent development in the field is the introduction of the…

eess.AS2024

WavCraft: Audio Editing and Generation with Large Language Models

Jinhua Liang, Huan Zhang, Haohe Liu +7

We introduce WavCraft, a collective system that leverages large language models (LLMs) to connect diverse task-specific models for audio content creation and editing. Specifically,…

eess.AS2023★ 8 cited

Acoustic Prompt Tuning: Empowering Large Language Models with Audition Capabilities

Jinhua Liang, Xubo Liu, Wenwu Wang +3

The auditory system plays a substantial role in shaping the overall human perceptual experience. While prevailing large language models (LLMs) and visual language models (VLMs) hav…

cs.SD2023

ATGNN: Audio Tagging Graph Neural Network

Shubhr Singh, Christian J. Steinmetz, Emmanouil Benetos +2

Deep learning models such as CNNs and Transformers have achieved impressive performance for end-to-end audio tagging. Recent works have shown that despite stacking multiple layers,…

cs.SD2023

A Deep Learning Architecture with Spatio-Temporal Focusing for Detecting Respiratory Anomalies

Dat Ngo, Lam Pham, Huy Phan +2

This paper presents a deep learning system applied for detecting anomalies from respiratory sound recordings. Our system initially performs audio feature extraction using Continuou…

eess.AS2023

Adapting Language-Audio Models as Few-Shot Audio Learners

Jinhua Liang, Xubo Liu, Haohe Liu +4

We presented the Treff adapter, a training-efficient adapter for CLAP, to boost zero-shot classification performance by making use of a small set of labelled data. Specifically, we…