Tacit-TTS: From Autoregressive Decoding to Masked Prediction for Efficient Transcript-Free Voice Cloning

arXiv:2609.38658 · eess.AS, cs.CL, cs.SD · Submitted 2026-09-29 · Read on arXiv

eess.AS, cs.CL, cs.SD

Submitted: 2026-09-29

Updated: 2026-09-29

Code: https://github.com/textstat/textstat

Terminology

• Distillation — 15× in this paper · explained in 2 episodes
• Transformer — 11× in this paper · explained in 2 episodes
• Embeddings — 9× in this paper · explained in 2 episodes
• Flow Matching — 4× in this paper · explained in 8 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Diffusion Model — 3× in this paper · explained in 8 episodes
• Diffusion Models — 3× in this paper · explained in 6 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Rectified Flow — 3× in this paper · explained in 3 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Commentary — 2× in this paper · explained in 2 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Knowledge Distillation — 2× in this paper · explained in 11 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Aphasia — 1× in this paper · explained in 1 episode
• Computational overhead — 1× in this paper · explained in 2 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Seed-TTS: A Family of High-Quality Versatile Speech Generation Models
• Seamless: Multilingual Expressive and Streaming Speech Translation
• SoundStorm: Efficient Parallel Audio Generation
• IndexTTS: An Industrial-Level Controllable and Efficient Zero-Shot Text-To-Speech System
• CosyVoice: A Scalable Multilingual Zero-shot Text-to-speech Synthesizer based on Supervised Semantic Tokens
• CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Models
• FunASR: A Fundamental End-to-End Speech Recognition Toolkit
• Distilling the Knowledge in a Neural Network
• BigVGAN: A Universal Neural Vocoder with Large-Scale Training
• Flow Matching for Generative Modeling
• Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
• FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
• UTMOS: UTokyo-SaruLab System for VoiceMOS Challenge 2022
• Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
• CAM++: A Fast and Efficient Network for Speaker Verification Using Context-Aware Masking
• Spark-TTS: An Efficient LLM-Based Text-to-Speech Model with Single-Stream Decoupled Speech Tokens

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• X-VC: Zero-shot Streaming Voice Conversion in Codec Space
• Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers
• Anonymization, Not Elimination: Utility-Preserved Speech Anonymization
• Towards Audio Token Compression in Large Audio Language Models
• WaveScat: Wavelet Scattering Front-Ends with Self-Supervised Features for Speech Deepfake Detection
• ProPS: Prompted Profile Synthesis for Natural Language-Conditioned Speaker Embedding Distributions