--- title: "dc_tts vs StyleTTS2" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/kyubyong-dc-tts-vs-yl4579-styletts2" tools: ["kyubyong-dc-tts", "yl4579-styletts2"] --- # dc_tts vs StyleTTS2 *GraphCanon updated Jul 30, 2026* ## Verdict Pick dc_tts if dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies; pick StyleTTS2 if styleTTS2 leverages style diffusion and GANs for superior speaker adaptation in text-to-speech applications. [dc_tts](https://github.com/Kyubyong/dc_tts) reports 1.2k GitHub stars, 360 forks, and 68 open issues, last pushed Apr 14, 2023. [StyleTTS2](https://github.com/yl4579/StyleTTS2) has 6.3k stars, 694 forks, and 118 open issues, last pushed Aug 10, 2024. Figures are from public GitHub metadata via [dc_tts's repository](https://github.com/Kyubyong/dc_tts) and [StyleTTS2's repository](https://github.com/yl4579/StyleTTS2). | | [dc_tts](/tools/kyubyong-dc-tts.md) | [StyleTTS2](/tools/yl4579-styletts2.md) | | --- | --- | --- | | Tagline | A TensorFlow Implementation of DC-TTS | StyleTTS 2 advances human-like text-to-speech using style diffusion and adversarial training. | | Stars | 1,156 | 6,322 | | Forks | 360 | 694 | | Open issues | 68 | 118 | | Language | Python | Python | | Adopt for | dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies. | StyleTTS2 leverages style diffusion and GANs for superior speaker adaptation in text-to-speech applications. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Speech & Audio | Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [dc_tts](/tools/kyubyong-dc-tts.md) | [StyleTTS2](/tools/yl4579-styletts2.md) | | --- | --- | --- | | Days since push | 1203d | 718d | | Open issues (now) | 68 | 118 | | Full report | [trust report](/tools/kyubyong-dc-tts/trust.md) | [trust report](/tools/yl4579-styletts2/trust.md) | ## Decision facts: dc_tts - **Requirements:** Depends on TensorFlow >=1.3 and has compatibility issues with updated APIs for `tf.contrib.layers.layer_norm`.; Requires Python packages like NumPy, librosa, tqdm, matplotlib, and scipy. - **Adopt for:** dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies. ## Decision facts: StyleTTS2 - **Adopt for:** StyleTTS2 leverages style diffusion and GANs for superior speaker adaptation in text-to-speech applications. ## Choose when ### Choose dc_tts if… - License: dc_tts is Apache-2.0, StyleTTS2 is MIT. - Requirements: Depends on TensorFlow >=1.3 and has compatibility issues with updated APIs for `tf.contrib.layers.layer_norm`.; Requires Python packages like NumPy, librosa, tqdm, matplotlib, and scipy.. - Tags unique to dc_tts: speech, speech-to-text, tensorflow. - dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies. ### Choose StyleTTS2 if… - License: StyleTTS2 is MIT, dc_tts is Apache-2.0. - Tags unique to StyleTTS2: adversarial training, deep-learning, diffusion-models, gan. - When you need highly natural speech synthesis with accurate speaker adaptation through advanced generative models ## When NOT to use dc_tts - Last GitHub push was 1229 days ago (dormant maintenance, Apr 14, 2023). Validate activity before betting a new project on dc_tts. ## When NOT to use StyleTTS2 - Avoid if requirements do not align with using models specifically trained on large speech language models - Do not use in contexts where explicit disclosure of synthesis is not feasible or appropriate as per ethical considerations ## Common questions ### What is the difference between dc_tts and StyleTTS2? dc_tts: A TensorFlow Implementation of DC-TTS. StyleTTS2: StyleTTS 2 advances human-like text-to-speech using style diffusion and adversarial training.. See the comparison table for live GitHub stats and shared categories. ### When should I choose dc_tts over StyleTTS2? Choose dc_tts over StyleTTS2 when License: dc_tts is Apache-2.0, StyleTTS2 is MIT; Requirements: Depends on TensorFlow >=1.3 and has compatibility issues with updated APIs for `tf.contrib.layers.layer_norm`.; Requires Python packages like NumPy, librosa, tqdm, matplotlib, and scipy.; Tags unique to dc_tts: speech, speech-to-text, tensorflow; dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies. ### When should I choose StyleTTS2 over dc_tts? Choose StyleTTS2 over dc_tts when License: StyleTTS2 is MIT, dc_tts is Apache-2.0; Tags unique to StyleTTS2: adversarial training, deep-learning, diffusion-models, gan; When you need highly natural speech synthesis with accurate speaker adaptation through advanced generative models. ### When should I avoid dc_tts? Last GitHub push was 1229 days ago (dormant maintenance, Apr 14, 2023). Validate activity before betting a new project on dc_tts. ### When should I avoid StyleTTS2? Avoid if requirements do not align with using models specifically trained on large speech language models Do not use in contexts where explicit disclosure of synthesis is not feasible or appropriate as per ethical considerations ### Is dc_tts or StyleTTS2 more popular on GitHub? StyleTTS2 has more GitHub stars (6,322 vs 1,156). Stars measure visibility, not whether either tool fits your constraints. ### Are dc_tts and StyleTTS2 open source? Yes - both are open-source projects on GitHub (dc_tts: Apache-2.0, StyleTTS2: MIT). ### Where can I find alternatives to dc_tts or StyleTTS2? GraphCanon lists graph-backed alternatives at [dc_tts alternatives](/tools/kyubyong-dc-tts/alternatives) and [StyleTTS2 alternatives](/tools/yl4579-styletts2/alternatives) ([dc_tts markdown twin](/tools/kyubyong-dc-tts/alternatives.md), [StyleTTS2 markdown twin](/tools/yl4579-styletts2/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/kyubyong-dc-tts-vs-yl4579-styletts2.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, dc_tts or StyleTTS2? dc_tts: Dormant. StyleTTS2: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for dc_tts and StyleTTS2? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [dc_tts trust report](/tools/kyubyong-dc-tts/trust); [StyleTTS2 trust report](/tools/yl4579-styletts2/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=kyubyong-dc-tts`](/api/graphcanon/graph?tool=kyubyong-dc-tts) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_