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Matcha-TTS: A fast TTS architecture with conditional flow matching

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arxiv 2309.03199 v2 pith:2A3XNTRK submitted 2023-09-06 eess.AS cs.HCcs.LGcs.SD

Shivam Mehta , Ruibo Tu , Jonas Beskow , Éva Székely , Gustav Eje Henter This is my paper · ORCID
classification eess.AScs.HCcs.LGcs.SD
keywords matcha-ttsmodelsmatchingarchitectureconditionalfastflowpre-trained
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We introduce Matcha-TTS, a new encoder-decoder architecture for speedy TTS acoustic modelling, trained using optimal-transport conditional flow matching (OT-CFM). This yields an ODE-based decoder capable of high output quality in fewer synthesis steps than models trained using score matching. Careful design choices additionally ensure each synthesis step is fast to run. The method is probabilistic, non-autoregressive, and learns to speak from scratch without external alignments. Compared to strong pre-trained baseline models, the Matcha-TTS system has the smallest memory footprint, rivals the speed of the fastest models on long utterances, and attains the highest mean opinion score in a listening test. Please see https://shivammehta25.github.io/Matcha-TTS/ for audio examples, code, and pre-trained models.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. SemBridge: Semantic Token Anchoring for Continuous-Latent Autoregressive Speech Generation

    eess.AS 2026-08 conditional novelty 7.0 of 10

    SemBridge supervises autoregressive states with discrete semantic tokens during training, improving content fidelity of continuous-latent speech generation without changing inference.

  2. CuteTTS: Efficient and High-Quality Speech Synthesis via Autoregressive Modeling of Continuous Latents

    cs.SD 2026-08 conditional novelty 5.0 of 10

    CuteTTS combines a semantically aligned causal VAE, patch-level autoregression, and guidance-step distillation to deliver efficient zero-shot voice cloning in a 0.2B-parameter streaming system.

  3. Confucius4-TTS: Transcript-Free Cross-Lingual Zero-Shot TTS with a Learnable Speaker Encoder

    cs.SD 2026-08 conditional novelty 4.0 of 10

    Confucius4-TTS performs transcript-free, cross-lingual zero-shot voice cloning in 14 languages with competitive intelligibility and speaker similarity.

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