10 citations · 17 across the 25 of their papers we have counts for
15 papers · 1 filter
Task Vector in TTS: Toward Emotionally Expressive Dialectal Speech Synthesis
Pengchao Feng, Yao Xiao, Ziyang Ma +5
Recent advances in text-to-speech (TTS) have yielded remarkable improvements in naturalness and intelligibility. Building on these achievements, research has increasingly shifted t…
STAR-Bench: Probing Deep Spatio-Temporal Reasoning as Audio 4D Intelligence
Zihan Liu, Zhikang Niu, Qiuyang Xiao +10
Despite rapid progress in Multi-modal Large Language Models and Large Audio-Language Models, existing audio benchmarks largely test semantics that can be recovered from text captio…
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…
SAC: Neural Speech Codec with Semantic-Acoustic Dual-Stream Quantization
Wenxi Chen, Xinsheng Wang, Ruiqi Yan +9
Speech codecs that convert continuous speech signals into discrete tokens have become essential for speech language models. However, existing codecs struggle to balance high-qualit…
UniVoice: Unifying Autoregressive ASR and Flow-Matching based TTS with Large Language Models
Wenhao Guan, Zhikang Niu, Ziyue Jiang +5
Large language models (LLMs) have demonstrated promising performance in both automatic speech recognition (ASR) and text-to-speech (TTS) systems, gradually becoming the mainstream…
Semantic-VAE: Semantic-Alignment Latent Representation for Better Speech Synthesis
Zhikang Niu, Shujie Hu, Jeongsoo Choi +8
Mel-spectrograms have been widely used in zero-shot text-to-speech (TTS); their inherent redundancy leads to inefficiency in text-speech alignment. Compact VAE-based latent represe…
Cross-Lingual F5-TTS: Towards Language-Agnostic Voice Cloning and Speech Synthesis
Qingyu Liu, Yushen Chen, Zhikang Niu +7
Flow-matching-based text-to-speech (TTS) models have shown high-quality speech synthesis. However, most current flow-matching-based TTS models still rely on reference transcripts c…
MeanAudio: Fast and Faithful Text-to-Audio Generation with Mean Flows
Xiquan Li, Junxi Liu, Yuzhe Liang +3
Recent years have witnessed remarkable progress in Text-to-Audio Generation (TTA), providing sound creators with powerful tools to transform inspirations into vivid audio. Yet desp…
Traceable TTS: Toward Watermark-Free TTS with Strong Traceability
Yuxiang Zhao, Yunchong Xiao, Yushen Chen +4
Recent advances in Text-To-Speech (TTS) technology have enabled synthetic speech to mimic human voices with remarkable realism, raising significant security concerns. This undersco…
Accelerating Flow-Matching-Based Text-to-Speech via Empirically Pruned Step Sampling
Qixi Zheng, Yushen Chen, Zhikang Niu +4
Flow-matching-based text-to-speech (TTS) models, such as Voicebox, E2 TTS, and F5-TTS, have attracted significant attention in recent years. These models require multiple sampling…
Accelerating Diffusion-based Text-to-Speech Model Training with Dual Modality Alignment
Jeongsoo Choi, Zhikang Niu, Ji-Hoon Kim +3
The goal of this paper is to optimize the training process of diffusion-based text-to-speech models. While recent studies have achieved remarkable advancements, their training dema…
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…
Towards Flow-Matching-based TTS without Classifier-Free Guidance
Yuzhe Liang, Wenzhe Liu, Chunyu Qiang +7
Flow matching has demonstrated strong generative capabilities and has become a core component in modern Text-to-Speech (TTS) systems. To ensure high-quality speech synthesis, Class…
EmoVoice: LLM-based Emotional Text-To-Speech Model with Freestyle Text Prompting
Guanrou Yang, Chen Yang, Qian Chen +12
Human speech goes beyond the mere transfer of information; it is a profound exchange of emotions and a connection between individuals. While Text-to-Speech (TTS) models have made h…
URO-Bench: Towards Comprehensive Evaluation for End-to-End Spoken Dialogue Models
Ruiqi Yan, Xiquan Li, Wenxi Chen +5
Recent advances in large language models (LLMs) have driven significant progress in end-to-end spoken dialogue models (SDMs). In contrast to text-based LLMs, the evaluation framewo…