SpeechEditBench provides seven atomic editing tasks, compositional multi-operation instructions, and an anchor-based protocol yielding target success, preservation success, and joint success metrics; evaluations show no model excels across dimensions and compositional editing is especially difficult
hub Mixed citations
Liu, ”Zero-shot Voice Conversion with Diffusion Transformers,”
Mixed citation behavior. Most common role is background (60%).
18
Pith papers citing it
Background
60% of classified citations
hub tools
citation-role summary
background 3
dataset 1
method 1
citation-polarity summary
verdicts
UNVERDICTED 18representative citing papers
Poly-SVC converts singing voices from polyphonic recordings while keeping melody, lyrics, and harmonies by combining CQT-based pitch extraction with a conditional flow matching diffusion decoder.
X-VC achieves zero-shot streaming voice conversion via one-step codec-space conversion with dual-conditioning acoustic converter and role-assignment training on generated paired data.
Voice conversion in interactive studies boosts user trust in SpeechLLM responses while automated metrics detect accent-by-gender disparities in alignment and verbosity.
ProsoCodec models prosody as a conditional residual in a speech codec via text and speaker prefix conditioning, yielding improved prosody preservation and less timbre leakage in voice conversion experiments.
A MoE-enhanced model with conditional distillation reduces speech-NVV EER from 38.93% to 22.66% and speech EER from 13.17% to 9.24% across 10 NVV types.
RTCFake is the first large-scale dataset of real-time communication speech deepfakes paired with offline versions, paired with a phoneme-guided consistency learning method that improves cross-platform and noise-robust detection.
Current video models succeed on basic understanding but achieve under 25% success on logically grounded generation and near 0% on interactive generation, exposing gaps in multimodal reasoning.
AugCodec disentangles speech into semantic, speaker, and prosody tokens via tailored data augmentations, achieving 12.5 Hz operation with three streams and outperforming prior codecs on LibriSpeech reconstruction and disentanglement metrics.
Zero-VC applies speaker anonymization as a perturbation to achieve strictly causal zero-lookahead streaming voice conversion by balancing timbre leakage against prosodic utility.
VibE-SVC2 extends prior singing voice conversion work with new modules for independent pitch-style and timbre-style control, claiming better performance and finer controllability than existing methods.
KNN retrieval over WavLM representations creates synthetic source-target pairs from non-parallel data for supervised voice conversion training with a speaker loss, achieving strong results on multilingual test sets despite English-only training.
Kimi-Audio is an open-source audio foundation model that achieves state-of-the-art results on speech recognition, audio understanding, question answering, and conversation after pre-training on more than 13 million hours of speech, sound, and music data.
Three data-centric strategies are studied to improve rare non-verbal vocalization recognition in ASR while preserving lexical accuracy.
Unified guidance framework for Flow Matching speech synthesis achieves nearly 3x faster inference and improved speaker similarity by combining heterogeneous data augmentation with intrinsic model guidance to eliminate CFG overhead.
MeanVC 2 introduces future-receptive chunking and a universal timbre token encoder to achieve lower-latency and more robust streaming zero-shot voice conversion than the original MeanVC.
AT-ADD introduces standardized tracks and datasets for evaluating audio deepfake detectors on speech under real-world conditions and on diverse unknown audio types to promote generalization beyond speech-centric methods.
A holistic survey of affective computing for intelligent agents covering emotion understanding via multimodal data, affective cognition, emotional expression synthesis, key challenges, and future directions emphasizing generative technologies.
citing papers explorer
-
SpeechEditBench: A Bilingual Multi-Attribute Benchmark for Instruction-Guided Speech Editing
SpeechEditBench provides seven atomic editing tasks, compositional multi-operation instructions, and an anchor-based protocol yielding target success, preservation success, and joint success metrics; evaluations show no model excels across dimensions and compositional editing is especially difficult
-
Poly-SVC: Polyphony-Aware Singing Voice Conversion with Harmonic Modeling
Poly-SVC converts singing voices from polyphonic recordings while keeping melody, lyrics, and harmonies by combining CQT-based pitch extraction with a conditional flow matching diffusion decoder.
-
X-VC: Zero-shot Streaming Voice Conversion in Codec Space
X-VC achieves zero-shot streaming voice conversion via one-step codec-space conversion with dual-conditioning acoustic converter and role-assignment training on generated paired data.
-
From Seeing it to Experiencing it: Interactive Evaluation of Intersectional Voice Bias in Human-AI Speech Interaction
Voice conversion in interactive studies boosts user trust in SpeechLLM responses while automated metrics detect accent-by-gender disparities in alignment and verbosity.
-
ProsoCodec: Prosody-Oriented Speech Codec for Voice Conversion
ProsoCodec models prosody as a conditional residual in a speech codec via text and speaker prefix conditioning, yielding improved prosody preservation and less timbre leakage in voice conversion experiments.
-
Speaker Identity in Non-Verbal Vocalizations: Conditional Distillation and Mixture of Experts Approach
A MoE-enhanced model with conditional distillation reduces speech-NVV EER from 38.93% to 22.66% and speech EER from 13.17% to 9.24% across 10 NVV types.
-
RTCFake: Speech Deepfake Detection in Real-Time Communication
RTCFake is the first large-scale dataset of real-time communication speech deepfakes paired with offline versions, paired with a phoneme-guided consistency learning method that improves cross-platform and noise-robust detection.
-
How Far Are Video Models from True Multimodal Reasoning?
Current video models succeed on basic understanding but achieve under 25% success on logically grounded generation and near 0% on interactive generation, exposing gaps in multimodal reasoning.
-
AugCodec: A Low-Bitrate Disentangled Neural Speech Codec via Data Augmentation
AugCodec disentangles speech into semantic, speaker, and prosody tokens via tailored data augmentations, achieving 12.5 Hz operation with three streams and outperforming prior codecs on LibriSpeech reconstruction and disentanglement metrics.
-
Zero-VC: Zero-Lookahead Streaming Voice Conversion via Speaker Anonymization
Zero-VC applies speaker anonymization as a perturbation to achieve strictly causal zero-lookahead streaming voice conversion by balancing timbre leakage against prosodic utility.
-
Vibrato Expression Control for Singing Voice Conversion with Improving Independent Control
VibE-SVC2 extends prior singing voice conversion work with new modules for independent pitch-style and timbre-style control, claiming better performance and finer controllability than existing methods.
-
From A to B to A: Palindromic Zero-Shot Voice Conversion with Non-Parallel Data
KNN retrieval over WavLM representations creates synthetic source-target pairs from non-parallel data for supervised voice conversion training with a speaker loss, achieving strong results on multilingual test sets despite English-only training.
-
Kimi-Audio Technical Report
Kimi-Audio is an open-source audio foundation model that achieves state-of-the-art results on speech recognition, audio understanding, question answering, and conversation after pre-training on more than 13 million hours of speech, sound, and music data.
-
Beyond Words: Towards Effective Modeling of Non-Verbal Vocalizations in ASR
Three data-centric strategies are studied to improve rare non-verbal vocalization recognition in ASR while preserving lexical accuracy.
-
Enhancing Flow Matching with A Unified Guidance Framework for Efficient and Robust Speech Synthesis
Unified guidance framework for Flow Matching speech synthesis achieves nearly 3x faster inference and improved speaker similarity by combining heterogeneous data augmentation with intrinsic model guidance to eliminate CFG overhead.
-
MeanVC 2: Robust Low-Latency Streaming Zero-Shot Voice Conversion
MeanVC 2 introduces future-receptive chunking and a universal timbre token encoder to achieve lower-latency and more robust streaming zero-shot voice conversion than the original MeanVC.
-
AT-ADD: All-Type Audio Deepfake Detection Challenge Evaluation Plan
AT-ADD introduces standardized tracks and datasets for evaluating audio deepfake detectors on speech under real-world conditions and on diverse unknown audio types to promote generalization beyond speech-centric methods.
-
Intelligent Agents with Emotional Intelligence: Current Trends, Challenges, and Future Prospects
A holistic survey of affective computing for intelligent agents covering emotion understanding via multimodal data, affective cognition, emotional expression synthesis, key challenges, and future directions emphasizing generative technologies.