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20162026
most citedImproving Trajectory Modelling for DNN-based Speech Synthesis by using Stacked Bottleneck Features and Minimum Generation Error Training

25 citations · 110 across the 42 of their papers we have counts for

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31 papers · 1 filter

cs.SD2026

Long-Prompt Zero-Shot TTS: Benchmarking Prosody Reproduction Beyond Voice Cloning

Dekun Chen, Renjie Xu, Yingda Shen +2

Zero-shot text-to-speech (TTS) typically conditions on a short speech prompt, which conveys timbre but provides only limited evidence of a speaker's prosodic patterns. We formulate…

cs.SD2026

What Matters in Preference Post-Training of Continuous Autoregressive Speech Language Models

Yingda Shen, Yao Qian, Dekun Chen +6

Continuous autoregressive speech language models combine an autoregressive (AR) backbone with a diffusion or flow-matching head. Preference post-training requires choosing how to c…

cs.SD2026

AnyEdit: A Unified Framework for Speech and Singing Voice Editing with Real-World Environmental Consistency

Yunjia Zhang, Junan Zhang, Jing Yang +3

We present AnyEdit, a unified, separation-free framework for speech and singing voice editing that preserves real-world acoustic environments, including noise, reverberation, and b…

cs.SD2026

Interpreting and Evaluating Dynamic-Rate Speech Codec Boundaries

Han Wang, Jiaqi Li, Yingda Shen +2

Dynamic-frame-rate neural speech codecs replace a uniform frame grid with variable-duration tokens, making boundary placement part of the representation itself. Yet it is unclear w…

cs.SD2026

CycleSpeech: Reciprocal Alignment for Instruction-Controlled Speech Synthesis and Paralinguistic Understanding

Huan Liao, Haonan Han, Xingwen Han +3

Instruction-controlled speech synthesis and paralinguistic understanding are often trained independently, leaving reciprocal feedback between the two tasks underexplored. We introd…

cs.SD2026

GenTraceBench: A Benchmark for Tracing Audio Deepfakes Across Pre- and Post-training Stages

Li Wang, Kunyu Feng, Wan Lin +7

Modern text-to-speech (TTS) systems are rarely deployed as unchanged pre-trained models. They are often adapted through supervised fine-tuning (SFT) or preference optimization such…

cs.SD2026

Multi-Dimensional Prosody Judgment For Live Streaming Speech Synthesis

Zifan Guan, Longyu Lu, Junan Zhang +3

Evaluating live streaming speech synthesis (TTS) requires assessing fine-grained, highly expressive prosody such as emotion, intonation, and energy which traditional MOS predictors…

cs.SD2026

CoReLoop: Parameter-Efficient Controlled Recurrent Refinement for Audio Deepfake Detection

Kunyu Feng, Yuxiang Wang, Li Wang +2

Audio deepfake detectors are expected to remain robust to diverse attacks, datasets, and recording conditions, yet collecting training data that cover every future condition is imp…

cs.SD2026

SimulS2ST-Omni: Data-Efficient Streaming Speech-to-Speech Translation via Explicit Trajectory Supervision

Rongshen He, Xinyu Liang, Dekun Chen +3

Long-form streaming speech-to-speech translation (S2ST) requires incremental, unbounded translation under strict latency constraints. Existing methods typically suffer from sentenc…

cs.SD2026

Teffic-Audio: Tell Fact from Fiction

Wan Lin, Li Wang, Jindong Wang +2

Speech deepfake detection has expanded in scope with increasingly heterogeneous spoofing mechanisms, including speech synthesis, voice conversion, vocoder reconstruction, and neura…

cs.SD2026

P-MUSE: Prompt-MIDI-Optional Model for Unified Instrumental Music Synthesis and Editing

Chong Jing, Junan Zhang, Jing Yang +3

MIDI-to-Music system renders the melody and rhythm of a target MIDI sequence into musical segment while cloning instrument timbre from a prompt recording. Existing systems typicall…

cs.SD2026

Is One Score Enough? Assessing Singing Quality of Songs with Temporal Score Curves

Yishan Lv, Jing Luo, Xinyu Yang +1

Singing Quality Assessment (SQA) has become increasingly important for practical multimedia applications and Music AI systems, yet existing studies predominantly focus on short sin…

cs.SD2026

Anysynth:Zero-Shot Instrument Cloning via In-Context Learning and Asymmetric Hierarchical Guidance

Chong Jing, Junan Zhang, Jing Yang +3

Zero-shot instrument cloning aims to render an arbitrary [Target MIDI] sequence with the acoustic identity of an unseen instrument given only a short [Reference Audio, Reference MI…

cs.SD2026

Zero-VC: Zero-Lookahead Streaming Voice Conversion via Speaker Anonymization

Yudong Li, Zihao Fang, Junwen Qiu +4

Streaming zero-shot voice conversion struggles to disentangle timbre from linguistic content without degrading utility or inflating latency. Current methods rely on information bot…

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, but existing systems use fixed frame rates (e.g., 25 or 12.5 Hz), overlooking speech's time-varying informatio…

cs.SD2026

Frequency-Aware Self-Supervised Music Representation Learning

Yicheng Gu, Junan Zhang, Jerry Li +2

Self-supervised learning (SSL) has emerged as an essential paradigm for music information retrieval (MIR). While current SSL models achieve state-of-the-art performance across vari…

cs.SD2026

EigeNet: Geometry-Informed Multi-Modal Learning for Few-shot Novel View RIR Prediction

Chong Jing, Zitong Lan, Junan Zhang +1

Predicting spatially varying Room Impulse Response (RIR) from sparse observations is a critical but highly challenging inverse problem for immersive spatial audio rendering. In thi…

cs.SD2025

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.SD2025

An Extensive Analysis of the Singing Voice Conversion Challenge 2025 Evaluation Results

Lester Phillip Violeta, Xueyao Zhang, Jiatong Shi +4

We present a thorough analysis of the findings of the latest iteration of the Singing Voice Conversion Challenge, a scientific event aiming to compare and understand different voic…

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

An Investigation of Time-Frequency Representation Discriminators for High-Fidelity Vocoder

Yicheng Gu, Xueyao Zhang, Liumeng Xue +2

Generative Adversarial Network (GAN) based vocoders are superior in both inference speed and synthesis quality when reconstructing an audible waveform from an acoustic representati…

cs.SD2024★ 1 cited

SingVisio: Visual Analytics of Diffusion Model for Singing Voice Conversion

Liumeng Xue, Chaoren Wang, Mingxuan Wang +3

In this study, we present SingVisio, an interactive visual analysis system that aims to explain the diffusion model used in singing voice conversion. SingVisio provides a visual di…

cs.SD2023★ 3 cited

Amphion: An Open-Source Audio, Music and Speech Generation Toolkit

Xueyao Zhang, Liumeng Xue, Yicheng Gu +16

Amphion is an open-source toolkit for Audio, Music, and Speech Generation, targeting to ease the way for junior researchers and engineers into these fields. It presents a unified f…