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20232026
most citedEMO-SUPERB: An In-depth Look at Speech Emotion Recognition

2 citations · 4 across the 13 of their papers we have counts for

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9 papers · 1 filter

cs.SD2026

Joint Fullband-Subband Modeling for High-Resolution SingFake Detection

Xuanjun Chen, Chia-Yu Hu, Sung-Feng Huang +3

Rapid advances in singing voice synthesis have increased unauthorized imitation risks, creating an urgent need for better Singing Voice Deepfake (SingFake) Detection, also known as…

cs.SD2025

How Does Instrumental Music Help SingFake Detection?

Xuanjun Chen, Chia-Yu Hu, I-Ming Lin +8

Although many models exist to detect singing voice deepfakes (SingFake), how these models operate, particularly with instrumental accompaniment, is unclear. We investigate how inst…

cs.SD2025

Localizing Audio-Visual Deepfakes via Hierarchical Boundary Modeling

Xuanjun Chen, Shih-Peng Cheng, Jiawei Du +6

Audio-visual temporal deepfake localization under the content-driven partial manipulation remains a highly challenging task. In this scenario, the deepfake regions are usually only…

cs.SD2025

Towards Generalized Source Tracing for Codec-Based Deepfake Speech

Xuanjun Chen, I-Ming Lin, Lin Zhang +3

Recent attempts at source tracing for codec-based deepfake speech (CodecFake), generated by neural audio codec-based speech generation (CoSG) models, have exhibited suboptimal perf…

cs.SD2025

Codec-Based Deepfake Source Tracing via Neural Audio Codec Taxonomy

Xuanjun Chen, I-Ming Lin, Lin Zhang +4

Recent advances in neural audio codec-based speech generation (CoSG) models have produced remarkably realistic audio deepfakes. We refer to deepfake speech generated by CoSG system…

cs.SD2025

CodecFake+: Codec-Based Resynthesized Data as a Proxy for Detecting CodecFake Speech

Xuanjun Chen, Jiawei Du, Haibin Wu +8

With the rapid advancement of neural audio codecs, codec-based speech generation (CoSG) systems have become highly powerful. Unfortunately, CoSG also enables the creation of highly…

cs.SD2024

Music2Fail: Transfer Music to Failed Recorder Style

Chon In Leong, I-Ling Chung, Kin-Fong Chao +3

The goal of music style transfer is to convert a music performance by one instrument into another while keeping the musical contents unchanged. In this paper, we investigate anothe…

cs.SD2024

DFADD: The Diffusion and Flow-Matching Based Audio Deepfake Dataset

Jiawei Du, I-Ming Lin, I-Hsiang Chiu +6

Mainstream zero-shot TTS production systems like Voicebox and Seed-TTS achieve human parity speech by leveraging Flow-matching and Diffusion models, respectively. Unfortunately, hu…

cs.SD2024

Improving Real-Time Music Accompaniment Separation with MMDenseNet

Chun-Hsiang Wang, Chung-Che Wang, Jun-You Wang +2

Music source separation aims to separate polyphonic music into different types of sources. Most existing methods focus on enhancing the quality of separated results by using a larg…