138 citations · 1.2k across the 72 of their papers we have counts for
49 papers · 1 filter
Behavior-Conditioned Animal Vocalization Generation: Event-Aware Modeling and Multidimensional Evaluation
Xinlong Deng, Yong Tian, Jian Guan +3
Behavior-conditioned animal vocalization generation aims to synthesize vocalizations from natural-language descriptions of animal behaviors, social interactions, and contexts. This…
MERTech: Instrument Playing Technique Detection Using Self-Supervised Pretrained Model With Multi-Task Finetuning
Dichucheng Li, Yinghao Ma, Weixing Wei +6
Instrument playing techniques (IPTs) constitute a pivotal component of musical expression. However, the development of automatic IPT detection methods suffers from limited labeled…
Transformer-based Autoencoder with ID Constraint for Unsupervised Anomalous Sound Detection
Jian Guan, Youde Liu, Qiuqiang Kong +4
Unsupervised anomalous sound detection (ASD) aims to detect unknown anomalous sounds of devices when only normal sound data is available. The autoencoder (AE) and self-supervised l…
AudioLDM 2: Learning Holistic Audio Generation with Self-supervised Pretraining
Haohe Liu, Yi Yuan, Xubo Liu +7
Although audio generation shares commonalities across different types of audio, such as speech, music, and sound effects, designing models for each type requires careful considerat…
WavJourney: Compositional Audio Creation with Large Language Models
Xubo Liu, Zhongkai Zhu, Haohe Liu +8
Despite breakthroughs in audio generation models, their capabilities are often confined to domain-specific conditions such as speech transcriptions and audio captions. However, rea…
Universal Source Separation with Weakly Labelled Data
Qiuqiang Kong, Ke Chen, Haohe Liu +4
Universal source separation (USS) is a fundamental research task for computational auditory scene analysis, which aims to separate mono recordings into individual source tracks. Th…
Jointist: Simultaneous Improvement of Multi-instrument Transcription and Music Source Separation via Joint Training
Kin Wai Cheuk, Keunwoo Choi, Qiuqiang Kong +5
In this paper, we introduce Jointist, an instrument-aware multi-instrument framework that is capable of transcribing, recognizing, and separating multiple musical instruments from…
Binaural Rendering of Ambisonic Signals by Neural Networks
Yin Zhu, Qiuqiang Kong, Junjie Shi +4
Binaural rendering of ambisonic signals is of broad interest to virtual reality and immersive media. Conventional methods often require manually measured Head-Related Transfer Func…
Neural Sound Field Decomposition with Super-resolution of Sound Direction
Qiuqiang Kong, Shilei Liu, Junjie Shi +5
Sound field decomposition predicts waveforms in arbitrary directions using signals from a limited number of microphones as inputs. Sound field decomposition is fundamental to downs…
Learning Temporal Resolution in Spectrogram for Audio Classification
Haohe Liu, Xubo Liu, Qiuqiang Kong +2
The audio spectrogram is a time-frequency representation that has been widely used for audio classification. One of the key attributes of the audio spectrogram is the temporal reso…
Surrey System for DCASE 2022 Task 5: Few-shot Bioacoustic Event Detection with Segment-level Metric Learning
Haohe Liu, Xubo Liu, Xinhao Mei +3
Few-shot audio event detection is a task that detects the occurrence time of a novel sound class given a few examples. In this work, we propose a system based on segment-level metr…
Jointist: Joint Learning for Multi-instrument Transcription and Its Applications
Kin Wai Cheuk, Keunwoo Choi, Qiuqiang Kong +5
In this paper, we introduce Jointist, an instrument-aware multi-instrument framework that is capable of transcribing, recognizing, and separating multiple musical instruments from…
A Track-Wise Ensemble Event Independent Network for Polyphonic Sound Event Localization and Detection
Jinbo Hu, Yin Cao, Ming Wu +4
Polyphonic sound event localization and detection (SELD) aims at detecting types of sound events with corresponding temporal activities and spatial locations. In this paper, a trac…
CWS-PResUNet: Music Source Separation with Channel-wise Subband Phase-aware ResUNet
Haohe Liu, Qiuqiang Kong, Jiafeng Liu
Music source separation (MSS) shows active progress with deep learning models in recent years. Many MSS models perform separations on spectrograms by estimating bounded ratio masks…
VoiceFixer: Toward General Speech Restoration with Neural Vocoder
Haohe Liu, Qiuqiang Kong, Qiao Tian +4
Speech restoration aims to remove distortions in speech signals. Prior methods mainly focus on single-task speech restoration (SSR), such as speech denoising or speech declipping.…
Decoupling Magnitude and Phase Estimation with Deep ResUNet for Music Source Separation
Qiuqiang Kong, Yin Cao, Haohe Liu +2
Deep neural network based methods have been successfully applied to music source separation. They typically learn a mapping from a mixture spectrogram to a set of source spectrogra…
A Unified Model for Zero-shot Music Source Separation, Transcription and Synthesis
Liwei Lin, Qiuqiang Kong, Junyan Jiang +1
We propose a unified model for three inter-related tasks: 1) to \textit{separate} individual sound sources from a mixed music audio, 2) to \textit{transcribe} each sound source to…
An Audio-Based Deep Learning Framework For BBC Television Programme Classification
Lam Pham, Chris Baume, Qiuqiang Kong +3
This paper proposes a deep learning framework for classification of BBC television programmes using audio. The audio is firstly transformed into spectrograms, which are fed into a…
Time-domain Speech Enhancement with Generative Adversarial Learning
Feiyang Xiao, Jian Guan, Qiuqiang Kong +1
Speech enhancement aims to obtain speech signals with high intelligibility and quality from noisy speech. Recent work has demonstrated the excellent performance of time-domain deep…
Speech enhancement with weakly labelled data from AudioSet
Qiuqiang Kong, Haohe Liu, Xingjian Du +3
Speech enhancement is a task to improve the intelligibility and perceptual quality of degraded speech signal. Recently, neural networks based methods have been applied to speech en…
CatNet: music source separation system with mix-audio augmentation
Xuchen Song, Qiuqiang Kong, Xingjian Du +1
Music source separation (MSS) is the task of separating a music piece into individual sources, such as vocals and accompaniment. Recently, neural network based methods have been ap…
CAA-Net: Conditional Atrous CNNs with Attention for Explainable Device-robust Acoustic Scene Classification
Zhao Ren, Qiuqiang Kong, Jing Han +2
Acoustic Scene Classification (ASC) aims to classify the environment in which the audio signals are recorded. Recently, Convolutional Neural Networks (CNNs) have been successfully…
Large-Scale MIDI-based Composer Classification
Qiuqiang Kong, Keunwoo Choi, Yuxuan Wang
Music classification is a task to classify a music piece into labels such as genres or composers. We propose large-scale MIDI based composer classification systems using GiantMIDI-…
An Improved Event-Independent Network for Polyphonic Sound Event Localization and Detection
Yin Cao, Turab Iqbal, Qiuqiang Kong +3
Polyphonic sound event localization and detection (SELD), which jointly performs sound event detection (SED) and direction-of-arrival (DoA) estimation, detects the type and occurre…