7 citations · 20 across the 18 of their papers we have counts for
19 papers
Qwen-Music Technical Report
Jin Xu, Kangdi Wang, Ruibin Yuan +24
We introduce Qwen-Music, a music generation model that produces high-fidelity songs with complete vocals. It supports text-to-music generation from descriptions, lyrics, and musica…
DiSTAR: Diffusion over a Scalable Token Autoregressive Representation for Speech Generation
Yakun Song, Xiaobin Zhuang, Jiawei Chen +8
Recent attempts to interleave autoregressive (AR) sketchers with diffusion-based refiners over continuous speech representations have shown promise, but they remain brittle under d…
Heptapod: Language Modeling on Visual Signals
Yongxin Zhu, Jiawei Chen, Yuanzhe Chen +6
We introduce Heptapod, an image autoregressive model that adheres to the foundational principles of language modeling. Heptapod employs \textbf{causal attention}, \textbf{eliminate…
DreamAudio: Customized Text-to-Audio Generation with Diffusion Models
Yi Yuan, Xubo Liu, Haohe Liu +5
With the development of large-scale diffusion-based and language-modeling-based generative models, impressive progress has been achieved in text-to-audio generation. Despite produc…
SplitMeanFlow: Interval Splitting Consistency in Few-Step Generative Modeling
Yi Guo, Wei Wang, Zhihang Yuan +8
Generative models like Flow Matching have achieved state-of-the-art performance but are often hindered by a computationally expensive iterative sampling process. To address this, r…
Sounding that Object: Interactive Object-Aware Image to Audio Generation
Tingle Li, Baihe Huang, Xiaobin Zhuang +6
Generating accurate sounds for complex audio-visual scenes is challenging, especially in the presence of multiple objects and sound sources. In this paper, we propose an {\em inter…
Towards Reliable Large Audio Language Model
Ziyang Ma, Xiquan Li, Yakun Song +8
Recent advancements in large audio language models (LALMs) have demonstrated impressive results and promising prospects in universal understanding and reasoning across speech, musi…
AudioMorphix: Training-free audio editing with diffusion probabilistic models
Jinhua Liang, Yuanzhe Chen, Yi Yuan +5
Editing sound with precision is a crucial yet underexplored challenge in audio content creation. While existing works can manipulate sounds by text instructions or audio exemplar p…
MMAR: A Challenging Benchmark for Deep Reasoning in Speech, Audio, Music, and Their Mix
Ziyang Ma, Yinghao Ma, Yanqiao Zhu +31
We introduce MMAR, a new benchmark designed to evaluate the deep reasoning capabilities of Audio-Language Models (ALMs) across massive multi-disciplinary tasks. MMAR comprises 1,00…
DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation
Dongya Jia, Zhuo Chen, Jiawei Chen +8
Several recent studies have attempted to autoregressively generate continuous speech representations without discrete speech tokens by combining diffusion and autoregressive models…
Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognition
Ye Bai, Jingping Chen, Jitong Chen +52
Modern automatic speech recognition (ASR) model is required to accurately transcribe diverse speech signals (from different domains, languages, accents, etc) given the specific con…
Sound-VECaps: Improving Audio Generation with Visual Enhanced Captions
Yi Yuan, Dongya Jia, Xiaobin Zhuang +9
Generative models have shown significant achievements in audio generation tasks. However, existing models struggle with complex and detailed prompts, leading to potential performan…
Seed-TTS: A Family of High-Quality Versatile Speech Generation Models
Philip Anastassiou, Jiawei Chen, Jitong Chen +43
We introduce Seed-TTS, a family of large-scale autoregressive text-to-speech (TTS) models capable of generating speech that is virtually indistinguishable from human speech. Seed-T…
VoiceShop: A Unified Speech-to-Speech Framework for Identity-Preserving Zero-Shot Voice Editing
Philip Anastassiou, Zhenyu Tang, Kainan Peng +6
We present VoiceShop, a novel speech-to-speech framework that can modify multiple attributes of speech, such as age, gender, accent, and speech style, in a single forward pass whil…
Audio Prompt Tuning for Universal Sound Separation
Yuzhuo Liu, Xubo Liu, Yan Zhao +4
Universal sound separation (USS) is a task to separate arbitrary sounds from an audio mixture. Existing USS systems are capable of separating arbitrary sources, given a few example…
InstructME: An Instruction Guided Music Edit And Remix Framework with Latent Diffusion Models
Bing Han, Junyu Dai, Weituo Hao +6
Music editing primarily entails the modification of instrument tracks or remixing in the whole, which offers a novel reinterpretation of the original piece through a series of oper…
Zero-Shot Accent Conversion using Pseudo Siamese Disentanglement Network
Dongya Jia, Qiao Tian, Kainan Peng +5
The goal of accent conversion (AC) is to convert the accent of speech into the target accent while preserving the content and speaker identity. AC enables a variety of applications…
Controllable and Lossless Non-Autoregressive End-to-End Text-to-Speech
Zhengxi Liu, Qiao Tian, Chenxu Hu +5
Some recent studies have demonstrated the feasibility of single-stage neural text-to-speech, which does not need to generate mel-spectrograms but generates the raw waveforms direct…
Neural Dubber: Dubbing for Videos According to Scripts
Chenxu Hu, Qiao Tian, Tingle Li +3
Dubbing is a post-production process of re-recording actors' dialogues, which is extensively used in filmmaking and video production. It is usually performed manually by profession…