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cs.SD2026

FlexiSLM: A Spoken Language Model with Dynamic and Controllable Frame Rates

Jiaqi Li, Chaoren Wang, Xiaohai Tian +9

Spoken language models (SLMs) extend LLMs to speech input and output. Existing SLMs represent speech at fixed frame rates (e.g., 25 or 12.5 Hz), ignoring the time-varying informati…

cs.SD2026

Aliasing-Free Neural Audio Synthesis

Yicheng Gu, Junan Zhang, Chaoren Wang +3

In neural audio synthesis, neural vocoders and codecs are models that reconstruct waveforms from acoustic and latent representations, which are essential to the resulting audio qua…

cs.SD2026

MimicLM: Zero-Shot Voice Imitation through Autoregressive Modeling of Pseudo-Parallel Speech Corpora

Tao Feng, Yuxiang Wang, Yuancheng Wang +5

Voice imitation aims to transform source speech to match a reference speaker's timbre and speaking style while preserving linguistic content. A straightforward approach is to train…

cs.SD2026

Vevo2: A Unified and Controllable Framework for Speech and Singing Voice Generation

Xueyao Zhang, Junan Zhang, Yuancheng Wang +5

Controllable human voice generation, particularly for expressive domains like singing, remains a significant challenge. This paper introduces Vevo2, a unified framework for control…

cs.SD2025

SpeechJudge: Towards Human-Level Judgment for Speech Naturalness

Xueyao Zhang, Chaoren Wang, Huan Liao +8

Aligning large generative models with human feedback is a critical challenge. In speech synthesis, this is particularly pronounced due to the lack of a large-scale human preference…

cs.SD2025

SP-MCQA: Evaluating Intelligibility of TTS Beyond the Word Level

Hitomi Jin Ling Tee, Chaoren Wang, Zijie Zhang +1

The evaluation of intelligibility for TTS has reached a bottleneck, as existing assessments heavily rely on word-by-word accuracy metrics such as WER, which fail to capture the com…