SwanBench-Speech is a new benchmark that decomposes long-form speech quality into seven disentangled metrics across 17 scenarios to evaluate generation models.
Glm-tts technical report
6 Pith papers cite this work. Polarity classification is still indexing.
6
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 6verdicts
UNVERDICTED 6roles
background 1polarities
background 1representative citing papers
HPRO uses a differentiable HD-Emo codec to extract separate content and style tokens and progressively aligns frame-, word-, and sentence-level rewards to improve emotional expressiveness in TTS while preserving intelligibility.
SwanVoice is a zero-shot TTS system for 1-4 speakers that reports higher richness and hierarchy scores than open-source baselines on monologue and dialogue tasks via mixed training and DiffusionNFT post-training.
A two-stage post-training pipeline of SFT followed by editing-oriented GRPO on unpaired data improves speech editing consistency and zero-shot TTS quality.
UniSonate unifies text-to-speech, text-to-music, and text-to-audio in a flow-matching framework with dynamic token injection and curriculum learning, reporting SOTA TTS and TTM results plus positive cross-task transfer.
OmniVoice introduces a diffusion language model-style non-autoregressive TTS system that directly maps text to multi-codebook acoustic tokens, scaling zero-shot synthesis to over 600 languages with SOTA results on multilingual benchmarks using 581k hours of open data.
citing papers explorer
-
Comprehensive Benchmarking of Long-Form Speech Generation in Diverse Scenarios
SwanBench-Speech is a new benchmark that decomposes long-form speech quality into seven disentangled metrics across 17 scenarios to evaluate generation models.
-
HPRO: Hierarchical Progressive Reward Optimization via Preference Extraction for Emotional Text-to-Speech
HPRO uses a differentiable HD-Emo codec to extract separate content and style tokens and progressively aligns frame-, word-, and sentence-level rewards to improve emotional expressiveness in TTS while preserving intelligibility.
-
SwanVoice: Expressive Long-Form Zero-Shot Speech Synthesis for Both Monologue and Dialogue
SwanVoice is a zero-shot TTS system for 1-4 speakers that reports higher richness and hierarchy scores than open-source baselines on monologue and dialogue tasks via mixed training and DiffusionNFT post-training.
-
CosyEdit2: Speech-Editing-Oriented Reinforcement Learning Unlocks Better Zero-Shot TTS
A two-stage post-training pipeline of SFT followed by editing-oriented GRPO on unpaired data improves speech editing consistency and zero-shot TTS quality.
-
UniSonate: A Unified Model for Speech, Music, and Sound Effect Generation with Text Instructions
UniSonate unifies text-to-speech, text-to-music, and text-to-audio in a flow-matching framework with dynamic token injection and curriculum learning, reporting SOTA TTS and TTM results plus positive cross-task transfer.
-
OmniVoice: Towards Omnilingual Zero-Shot Text-to-Speech with Diffusion Language Models
OmniVoice introduces a diffusion language model-style non-autoregressive TTS system that directly maps text to multi-codebook acoustic tokens, scaling zero-shot synthesis to over 600 languages with SOTA results on multilingual benchmarks using 581k hours of open data.