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Comparison

TTS vs WaveRNN

Verdict

Pick TTS when license: TTS is MPL-2.0, WaveRNN is MIT; pick WaveRNN when license: WaveRNN is MIT, TTS is MPL-2.0.

Markdown twin · TTS alternatives · WaveRNN alternatives

GraphCanon updated today

TTS logo

TTS

coqui-ai/TTS

★ 46kpushed Aug 16, 2024
vs
WaveRNN logo

WaveRNN

fatchord/WaveRNN

★ 2.2kpushed Jul 2, 2022

Trust & integrity

SignalTTSWaveRNN
Maintenance
Dormant (693d since push)
As of today · github_public_v1
Dormant (1469d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
137 low (137 low)
As of today · osv@v1
No criticals
As of today · osv@v1
TTS trust reportWaveRNN trust reportTrust methodology

Tagline

TTS
🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
WaveRNN
WaveRNN Vocoder + TTS

Stars

TTS
46k
WaveRNN
2.2k

Forks

TTS
6.2k
WaveRNN
687

Open issues

TTS
4
WaveRNN
108

Language

TTS
Python
WaveRNN
Python

Adopt for

TTS
-
WaveRNN
-

Persona

TTS
-
WaveRNN
-

Runtime

TTS
-
WaveRNN
-

License

TTS
MPL-2.0
WaveRNN
MIT

Last pushed

TTS
Aug 16, 2024
WaveRNN
Jul 2, 2022

Categories

TTS
Model Training, Speech & Audio, Inference & Serving
WaveRNN
Model Training, Speech & Audio

Trust and health

Days since push

TTS
693d
WaveRNN
1469d

Open issues (now)

TTS
4
WaveRNN
108

Owner type

TTS
Organization
WaveRNN
User

Security scan

TTS
137 low (137 low)
WaveRNN
No criticals

Full report

TTS
Trust report
WaveRNN
Trust report

Shared compatibility

  • Python · TTS: Python runtime · WaveRNN: Python runtime

Choose TTS if…

  • License: TTS is MPL-2.0, WaveRNN is MIT.
  • Tags unique to TTS: deep-learning, glow-tts, hifigan, speaker-encoder.
  • Also covers Inference & Serving.
  • TTS ships Docker support for self-hosted deployment.

When NOT to use TTS

  • Last GitHub push was 694 days ago (dormant maintenance, Aug 16, 2024). Validate activity before betting a new project on TTS.
  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
GitHubDetails

Choose WaveRNN if…

  • License: WaveRNN is MIT, TTS is MPL-2.0.
  • Tags unique to WaveRNN: tacotron, text-to-speech, tts, speech-synthesis.

When NOT to use WaveRNN

  • Last GitHub push was 1470 days ago (dormant maintenance, Jul 2, 2022). Validate activity before betting a new project on WaveRNN.
  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
GitHubDetails

Explore

TTS trust report →WaveRNN trust report →Model Training category →Speech & Audio category →Inference & Serving category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: TTS 46k · WaveRNN 2.2k (synced Jul 11, 2026).

Common questions

What is the difference between TTS and WaveRNN?
TTS: 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production. WaveRNN: WaveRNN Vocoder + TTS. See the comparison table for live GitHub stats and shared categories.
When should I choose TTS over WaveRNN?
Choose TTS over WaveRNN when License: TTS is MPL-2.0, WaveRNN is MIT; Tags unique to TTS: deep-learning, glow-tts, hifigan, speaker-encoder; Also covers Inference & Serving; TTS ships Docker support for self-hosted deployment.
When should I choose WaveRNN over TTS?
Choose WaveRNN over TTS when License: WaveRNN is MIT, TTS is MPL-2.0; Tags unique to WaveRNN: tacotron, text-to-speech, tts, speech-synthesis.
When should I avoid TTS?
Last GitHub push was 694 days ago (dormant maintenance, Aug 16, 2024). Validate activity before betting a new project on TTS. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
When should I avoid WaveRNN?
Last GitHub push was 1470 days ago (dormant maintenance, Jul 2, 2022). Validate activity before betting a new project on WaveRNN. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Is TTS or WaveRNN more popular on GitHub?
TTS has more GitHub stars (45,737 vs 2,187). Stars measure visibility, not whether either tool fits your constraints.
Are TTS and WaveRNN open source?
Yes - both are open-source projects on GitHub (TTS: MPL-2.0, WaveRNN: MIT).
Where can I find alternatives to TTS or WaveRNN?
GraphCanon lists graph-backed alternatives at TTS alternatives and WaveRNN alternatives (TTS markdown twin, WaveRNN markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, TTS or WaveRNN?
TTS: Dormant. WaveRNN: 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 TTS and WaveRNN?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: TTS trust report; WaveRNN trust report.