TTS Synthesis

TTS: Text-to-Speech

Text-to-speech synthesis studies how to turn written language into speech while preserving words, pronunciation, and the intended voice and delivery. Systems range from autoregressive models that generate speech tokens in sequence to parallel methods such as flow matching and diffusion, often using speaker prompts, phonetic alignment, or prosody controls. Current work extends these methods to multilingual and low-resource languages, expressive speech, long-form output, and low-latency streaming. A central challenge is balancing intelligibility, naturalness, speaker identity, and fine-grained control, while evaluations based on overall quality scores may miss errors in pronunciation, accent, or context.

Latest papers

275 papers49 papers in the last four weeks, up 17% on the four weeks before. 0.3% of all new papers.

When the Persona Contradicts the Line: Diagnosing Plan-to-Synthesis Failures in Chain-of-Thought TTS
Oct 26, 2026Joonyong Park, Jerry LiTTS Synthesis Emotional Speech Synthesis
Spellbrush, CA, USA
ImageTTS: Repurposing Pretrained Image Diffusion Transformers for Speech Synthesis
Oct 26, 2026Hanchen Pei, Shujie Liu, Yayue Deng +4TTS Synthesis Zero-Shot TTS
Electronic Information School, Wuhan University, Wuhan, China · Microsoft Corporation, Redmond, US · The Chinese University of Hong Kong, Hong Kong, China
LeanTTS: Efficient Full-Stack Bilingual TTS for Zero-Shot Cloning and Voice Customization
Oct 25, 2026Yuheng Lu, Qiulin Li, Xi Wang +5TTS Synthesis Zero-Shot TTS
Tianjin University, Tianjin, China · Didichuxing Co. Ltd., Beijing, China · Tsinghua University, Beijing, China
HeyGen Voice: Scene-Aware Voice Cloning for Talking Videos
Oct 21, 2026Pavel Andreev, Andrei Gusev, Adithya Narayan +15Voice Cloning TTS Synthesis
HeyGen Research
Character-Level Prosody Control for Mandarin Speech Synthesis:An Architecture-Preserving Approach
Oct 21, 2026Diankun An, Lu Ma, Yongliang Wang +2TTS Synthesis Speech Prosody
JD.com, Inc., Beijing, China
LoCA: Local Credit Assignment for Reinforcement Learning of Autoregressive Flow-Matching TTS
Oct 20, 2026Jie Liu, Junyu Zhou, Junhao Zhong +5TTS Synthesis Credit Assignment
Lingguang Zhaxian Technology, Shanghai, China
Steering intonational tunes in text-to-speech synthesis
Oct 19, 2026Juan Pablo Vigneaux, Jennifer ColeTTS Synthesis Speech Prosody
Northwestern University
MixiSpeech: Progressive State Distillation for One-Step Vietnamese TTS
Oct 18, 2026Tran Quoc Bao Le, Binh Mai, Hung Dinh +2TTS Synthesis Multi-Speaker TTS
Posts and Telecommunications Institute of Technology, Hanoi, Vietnam
Does Expert Supervision Improve Text-to-Speech? An Empirical Study of Preference Optimization
Oct 18, 2026Minh Duc Vu, Junchuan Zhao, Ye WangTTS Synthesis Text-to-Speech
Department of Statistics & Data Science, National University of Singapore, Singapore · School of Computing, National University of Singapore, Singapore
ShlokaDhara: A Multi-Speaker Sanskrit Speech Corpus for Learning Meter-Aware Prosody in Text-to-Recitation
Oct 17, 2026Harshal Kausadikar, Onkar Kishor Susladkar, Prathmesh Santosh Choudhari +3Speech Processing TTS Synthesis
Independent Researcher · University of Illinois at Urbana-Champaign · University of Florida +2
Vocal-Tract Acoustics, Aerodynamics, and Overlap-and-Add Synthesis in DYNARTmo
Oct 17, 2026Bernd J. KrögerControllable Speech Generation TTS Synthesis
Medical School, RWTH Aachen University, Aachen, Germany · Kröger Lab, Belgium, www.speechtrainer.eu
Pronouncing Hard Words: Phoneme Adaptation of a Pretrained Conversational Text to Speech Model
Oct 16, 2026Yashish M. Siriwardena, Dinesh K. Gnanasekaran, Tanmay Laud +3TTS Synthesis Controllable Speech Generation
Hippocratic AI · Carnegie Mellon University
Beyond the Benchmark: Conditioning, Domains and Failure Modes of Qwen3-TTS
Oct 16, 2026Séverin Baroudi, Yanis Labrak, Petr Motlicek +2TTS Synthesis Voice Cloning
Univ Toulon, Aix Marseille Univ, LIS, CNRS, France · Mila – Quebec AI Institute · Idiap Research Institute, Martigny, Switzerland +3
DriftTTS: One-stage Single Step Text-to-Speech via Generative Drifting
Oct 16, 2026Jaehyun Ahn, Dohyun Kim, Heeseung KimTTS Synthesis One-Step Generative Modeling
Department of AI, University of Seoul, Seoul, South Korea
Noise-Aware Lombard Speech Synthesis via Flow-GRPO for Intelligibility Optimization
Oct 14, 2026Zhaoyang Wang, Dingding Yao, Chengzhong Wang +1TTS Synthesis
Key Laboratory of Speech Acoustics and Content Understanding, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China, and also with University of Chinese Academy of Sciences, Beijing 100049, China.
Speaking Longer Than Learned: Training-Free Long-Form Generation for Full-Stream Text-to-Speech
Oct 14, 2026Jeseung Lim, Jiseong Woo, Heeseung KimLong-Form TTS Synthesis TTS Synthesis
Department of Physics, University of Seoul, Seoul, Republic of Korea · Department of AI, University of Seoul, Seoul, Republic of Korea
Revise-TTS: A Non-Masking Refinement Framework for Masked Diffusion Models in Text-to-Speech
Oct 14, 2026Wanli Sun, Dan Su, Anton RagniTTS Synthesis Zero-Shot TTS
School of Computer Science, University of Sheffield, Sheffield, UK · HojoAI, Beijing, China
Fish Audio Drama 3 Technical Report
Oct 13, 2026Dawei Han, Shidong Li, Shijia Liao +13TTS Synthesis Controllable Speech Generation
Beyond Fixed Targets: On-Policy One-Shot Speaker Personalization for Autoregressive Text-To-Speech Models
Oct 13, 2026Sangkwon Park, Che Hyun Lee, Heeseung Kim +1TTS Synthesis On-Policy Self-Distillation
ECE, Seoul National University · University of Seoul · IPAI, AIIS, ASRI, INMC, and ISRC, Seoul National University
GAMW: Generation-Aware Mel-Domain Watermarking for TTS Traceability
Oct 10, 2026Yihang Zhang, Weicai Yan, Qifei Zhang +2Audio Watermarking Robust Watermarking
Zhejiang University
Cross-Lingual TTS for Indian Languages: A Benchmark and Inference-Time Duration Estimation Strategies
Oct 10, 2026Adarsh Arigala, Arjun Gangwar, Srinivasan UmeshMultilingual TTS Synthesis TTS Synthesis
SPRING Lab, Indian Institute of Technology Madras, India
Training a Compact, Strong, and Realistic Text-to-Speech Model
Oct 10, 2026Runyuan Cai, Yu Lin, Yiming Wang +1TTS Synthesis Zero-Shot TTS
AutoArk
VoTSpeech: Decoupling Voice Design from Speech Generation in Instruction-Following TTS
Oct 10, 2026Wenbing Yang, Qihang Lu, Zihan Sun +4TTS Synthesis Controllable Speech Generation
Beijing University of Posts and Telecommunications, Beijing, China · Hello Group, Beijing, China
AphaVoice: Text-to-Speech Model for Aphasia Patient Simulation
Oct 10, 2026Al Varrel Putra Kusuma, Fernando Bello, Joshua BrownTTS Synthesis Clinical Speech Processing
Imperial College London, United Kingdom
Enhancing Speech Recognition through Text-to-Speech and Voice Conversion Augmentation
Oct 9, 2026Yunus Emre Ozkose, Ali HaznedarogluAutomatic Speech Recognition Synthetic Data Augmentation for Speech Recognition
Sestek, Istanbul, Turkey
E3-System: Expressive EmoData, Explicitly Controllable, Easy-to-Use TTS
Oct 9, 2026Yiqiao Huang, Xiaolong Lin, Zhenpeng Zhan +1TTS Synthesis Expressive Speech Synthesis
Harvard University, Cambridge, MA, USA · Baidu Inc., Shenzhen, China · The Chinese University of Hong Kong, Shenzhen, China
Beyond Speech Captions: Speech-Rewarded Style Planning for Conversational Text-to-Speech
Oct 8, 2026Shiao Zhu, Lianbo Liu, Sizhen Lyu +3TTS Synthesis Controllable Speech Generation
Institute of Science Tokyo, Tokyo, Japan · Independent Researcher, Tokyo, Japan
Edit Who Speaks, Control How They Speak: Global Timbre Editing and Local Instruction Control for TTS
Oct 8, 2026Junchuan Zhao, Chenglin Xu, Wei Zeng +3TTS Synthesis Controllable Speech Generation
National University of Singapore · LIGHTSPEED · Nanyang Technological University +1
Steerspeech: Activation Steering For Emotion Control In Generated Speech
Oct 7, 2026Afsara Benazir, Darius Pétermann, Felix Xiaozhu Lin +1Controllable Speech Generation Emotional Speech Synthesis
University of Virginia · Netflix, Inc.
Training-Free Instruction TTS Gender Bias Calibration Using Model-Adaptive Steering
Oct 7, 2026Kuan-Yu Chen, Yi-Cheng Lin, Jeng-Lin Li +1Text-to-Speech TTS Synthesis
AI Research Center, Inventec Corporation, Taiwan · Graduate Institute of Communication Engineering, National Taiwan University, Taiwan

Oct 26, 2026J/K move · Enter open · S save

When the Persona Contradicts the Line: Diagnosing Plan-to-Synthesis Failures in Chain-of-Thought TTS

Joonyong Park, Jerry Li

Spellbrush, CA, USA

TTS Synthesis Emotional Speech Synthesis TTS Evaluation Multilingual TTS Synthesis

Open paper AskPDF arXiv

Chain-of-thought TTS systems rely on language-model planners to translate persona and context into vocal delivery, but it is unclear where this intent is lost when the requested affect conflicts with lexical sentiment. We introduce a bilingual Japanese--English persona--line conflict benchmark in which each item pairs one line with congruent and conflicting personas and pre-declares the expected acoustic direction. We probe this direction in the planner-generated delivery phrase, the planner-written emotion vector, the QwenEmotion-generated vector, and the rendered waveform. Planner outputs are usually direction-correct, while downstream agreement can be substantially lower. Bypassing QwenEmotion provides only modest gains over the full planner-controlled Base. Supervising QwenEmotion raises the direction rate to 75% in Japanese and 84% in English. A learned text-to-latent interface reaches the highest English rate of 89% and the highest Japanese arousal rate of 88%. These results show that learned repair of the plan-to-synthesis interface can recover counter-textual delivery, although its effect differs across languages and acoustic axes.