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20212026
most citedEnhance Temporal Relations in Audio Captioning with Sound Event Detection

11 citations · 30 across the 24 of their papers we have counts for

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cs.SD2026

AlignAudio: A Unified Dual-Alignment Framework for Noise-Robust Speech-Conditioned Generation

Yixuan Li, Xuenan Xu, Zeyu Xie +1

Speech-conditioned generation maps speech signals to target audio outputs. Prior end-to-end speech-conditioned generative models achieve high fidelity in clean acoustic conditions,…

cs.SD2026

AuK Technical Report: An Open-Source Foundational Model for Speech Generation and Editing

Ziyang Ma, Zhikang Niu, Wenming Tu +30

We introduce AuK, an open-source foundational model that unifies speech generation and editing through a common interface of natural-language instructions and audio context. To sup…

cs.SD2026

MMAE: A Massive Multitask Audio Editing Benchmark

Ziyang Ma, Ruiqi Yan, Ruiyang Xu +35

We introduce MMAE, a Massive Multitask Audio Editing benchmark, serving as the first comprehensive evaluation testbed designed for general-purpose instruction-based audio editing.…

cs.SD2026★ 1 cited

Covo-Audio Technical Report

Wenfu Wang, Chenxing Li, Liqiang Zhang +23

In this work, we present Covo-Audio, a 7B-parameter end-to-end LALM that directly processes continuous audio inputs and generates audio outputs within a single unified architecture…

cs.SD2026

SemanticVocoder: Bridging Audio Generation and Audio Understanding via Semantic Latents

Zeyu Xie, Chenxing Li, Qiao Jin +6

Recent audio generation models typically rely on Variational Autoencoders (VAEs) and perform generation within the VAE latent space. Although VAEs excel at compression and reconstr…

cs.SD2025

PicoAudio2: Temporal Controllable Text-to-Audio Generation with Natural Language Description

Zihao Zheng, Zeyu Xie, Xuenan Xu +3

While recent work in controllable text-to-audio (TTA) generation has achieved fine-grained control through timestamp conditioning, its scope remains limited by audio quality and in…

cs.SD2025

LARA-Gen: Enabling Continuous Emotion Control for Music Generation Models via Latent Affective Representation Alignment

Jiahao Mei, Xuenan Xu, Shimeng Li +7

Recent advances in text-to-music models have enabled coherent music generation from text prompts, yet fine-grained emotional control remains unresolved. We introduce LARA-Gen, a fr…

cs.SD2025

When Audio Generators Become Good Listeners: Generative Features for Understanding Tasks

Zeyu Xie, Chenxing Li, Xuenan Xu +6

This work pioneers the utilization of generative features in enhancing audio understanding. Unlike conventional discriminative features that directly optimize posterior and thus em…

cs.SD2025

UniFlow-Audio: Unified Flow Matching for Audio Generation from Omni-Modalities

Xuenan Xu, Jiahao Mei, Zihao Zheng +9

Audio generation, including speech, music and sound effects, has advanced rapidly in recent years. These tasks can be divided into two categories: time-aligned (TA) tasks, where ea…

cs.SD2025

FakeSound2: A Benchmark for Explainable and Generalizable Deepfake Sound Detection

Zeyu Xie, Yaoyun Zhang, Xuenan Xu +4

The rapid development of generative audio raises ethical and security concerns stemming from forged data, making deepfake sound detection an important safeguard against the malicio…

cs.SD2025

STAR: Speech-to-Audio Generation via Representation Learning

Zeyu Xie, Xuenan Xu, Yixuan Li +2

This work presents STAR, the first end-to-end speech-to-audio generation framework, designed to enhance efficiency and address error propagation inherent in cascaded systems. Unlik…

cs.SD2025

Overview of the Amphion Toolkit (v0.2)

Jiaqi Li, Xueyao Zhang, Yuancheng Wang +9

Amphion is an open-source toolkit for Audio, Music, and Speech Generation, designed to lower the entry barrier for junior researchers and engineers in these fields. It provides a v…

cs.SD2024

DiveSound: LLM-Assisted Automatic Taxonomy Construction for Diverse Audio Generation

Baihan Li, Zeyu Xie, Xuenan Xu +5

Audio generation has attracted significant attention. Despite remarkable enhancement in audio quality, existing models overlook diversity evaluation. This is partially due to the l…

cs.SD2024★ 1 cited

PicoAudio: Enabling Precise Timestamp and Frequency Controllability of Audio Events in Text-to-audio Generation

Zeyu Xie, Xuenan Xu, Zhizheng Wu +1

Recently, audio generation tasks have attracted considerable research interests. Precise temporal controllability is essential to integrate audio generation with real applications.…

cs.SD2024

AudioTime: A Temporally-aligned Audio-text Benchmark Dataset

Zeyu Xie, Xuenan Xu, Zhizheng Wu +1

Recent advancements in audio generation have enabled the creation of high-fidelity audio clips from free-form textual descriptions. However, temporal relationships, a critical feat…

cs.SD2024

FakeSound: Deepfake General Audio Detection

Zeyu Xie, Baihan Li, Xuenan Xu +3

With the advancement of audio generation, generative models can produce highly realistic audios. However, the proliferation of deepfake general audio can pose negative consequences…

cs.SD2024

A Detailed Audio-Text Data Simulation Pipeline using Single-Event Sounds

Xuenan Xu, Xiaohang Xu, Zeyu Xie +3

Recently, there has been an increasing focus on audio-text cross-modal learning. However, most of the existing audio-text datasets contain only simple descriptions of sound events.…

cs.SD2024

Enhancing Audio Generation Diversity with Visual Information

Zeyu Xie, Baihan Li, Xuenan Xu +2

Audio and sound generation has garnered significant attention in recent years, with a primary focus on improving the quality of generated audios. However, there has been limited re…

cs.SD2024

Phonetic and Lexical Discovery of a Canine Language using HuBERT

Xingyuan Li, Sinong Wang, Zeyu Xie +2

This paper delves into the pioneering exploration of potential communication patterns within dog vocalizations and transcends traditional linguistic analysis barriers, which heavil…

cs.SD2023★ 11 cited

Enhance Temporal Relations in Audio Captioning with Sound Event Detection

Zeyu Xie, Xuenan Xu, Mengyue Wu +1

Automated audio captioning aims at generating natural language descriptions for given audio clips, not only detecting and classifying sounds, but also summarizing the relationships…

cs.SD2023

BLAT: Bootstrapping Language-Audio Pre-training based on AudioSet Tag-guided Synthetic Data

Xuenan Xu, Zhiling Zhang, Zelin Zhou +4

Compared with ample visual-text pre-training research, few works explore audio-text pre-training, mostly due to the lack of sufficient parallel audio-text data. Most existing metho…

cs.SD2022★ 2 cited

Beyond the Status Quo: A Contemporary Survey of Advances and Challenges in Audio Captioning

Xuenan Xu, Zeyu Xie, Mengyue Wu +1

Automated audio captioning (AAC), a task that mimics human perception as well as innovatively links audio processing and natural language processing, has overseen much progress ove…

cs.SD2021★ 7 cited

Can Audio Captions Be Evaluated with Image Caption Metrics?

Zelin Zhou, Zhiling Zhang, Xuenan Xu +3

Automated audio captioning aims at generating textual descriptions for an audio clip. To evaluate the quality of generated audio captions, previous works directly adopt image capti…

cs.SD2021★ 8 cited

Investigating Local and Global Information for Automated Audio Captioning with Transfer Learning

Xuenan Xu, Heinrich Dinkel, Mengyue Wu +2

Automated audio captioning (AAC) aims at generating summarizing descriptions for audio clips. Multitudinous concepts are described in an audio caption, ranging from local informati…