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Comparison

WaveRNN vs dc_tts

Verdict

Pick WaveRNN if waveRNN is a Python-based neural vocoder that can generate high-quality speech from text when used with TTS models like Tacotron; pick dc_tts if dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies.

Markdown twin · WaveRNN alternatives · dc_tts alternatives

GraphCanon updated Sep 20, 2026

8views this month

WaveRNN logo

WaveRNN

fatchord/WaveRNN

★ 2.2kpushed Jul 2, 2022
vs
dc_tts logo

dc_tts

Kyubyong/dc_tts

★ 1.2kpushed Apr 14, 2023

Trust & integrity

SignalWaveRNNdc_tts
Maintenance
Dormant (1540d since push)
As of Sep 20, 2026 · github_public_v1
Dormant (1254d since push)
As of Sep 20, 2026 · github_public_v1
Provenance
Not a fork · Personal account
As of Sep 20, 2026 · github_public_v1
Not a fork · Personal account
As of Sep 20, 2026 · github_public_v1
OSV dependency advisories
No published findings from this source as of 2026-07-11
As of Jul 11, 2026 · osv@v1
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1
WaveRNN trust reportdc_tts trust reportTrust methodology

Tagline

WaveRNN
WaveRNN Vocoder + TTS
dc_tts
A TensorFlow Implementation of DC-TTS

Stars

WaveRNN
2.2k
dc_tts
1.2k

Forks

WaveRNN
685
dc_tts
360

Open issues

WaveRNN
108
dc_tts
68

Language

WaveRNN
Python
dc_tts
Python

Adopt for

WaveRNN
WaveRNN is a Python-based neural vocoder that can generate high-quality speech from text when used with TTS models like Tacotron.
dc_tts
dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies.

Persona

WaveRNN
-
dc_tts
-

Runtime

WaveRNN
-
dc_tts
-

License

WaveRNN
MIT
dc_tts
Apache-2.0

Last pushed

WaveRNN
Jul 2, 2022
dc_tts
Apr 14, 2023

Categories

WaveRNN
Speech & Audio
dc_tts
Speech & Audio

Trust and health

Days since push

WaveRNN
1540d
dc_tts
1254d

Open issues (now)

WaveRNN
108
dc_tts
68

Stars delta

WaveRNN
+1 (30d)
dc_tts
+3 (30d)

OSV dependency advisories

WaveRNN
No published findings from this source as of 2026-07-11
dc_tts
No lockfile (source not queried)

Full report

WaveRNN
Trust report
dc_tts
Trust report

Choose WaveRNN if…

  • License: WaveRNN is MIT, dc_tts is Apache-2.0.
  • Requirements: Python version must be equal to or higher than 3.6; Pytorch 1 with CUDA support is a prerequisite.
  • Tags unique to WaveRNN: neural-vocoder, pytorch, speech-synthesis, tacotron.
  • When you require a compact and efficient method to produce natural-sounding speech synthesis, specifically with the need for high fidelity in audio quality.

When NOT to use WaveRNN

  • Avoid using when you need extensive customization of the vocoder parameters, since it is optimized for specific configurations and might not offer the level of tweakability other frameworks provide.
  • Not recommended if your setup does not support CUDA, as WaveRNN requires PyTorch with CUDA for execution.
GitHubDetails

Choose dc_tts if…

  • License: dc_tts is Apache-2.0, WaveRNN 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 NOT to use dc_tts

  • Last GitHub push was Apr 14, 2023 (dormant maintenance). Validate activity before betting a new project on dc_tts.
GitHubDetails

Explore

WaveRNN trust report →dc_tts trust report →Speech & Audio 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: WaveRNN 2.2k · dc_tts 1.2k (synced Sep 20, 2026).

Common questions

What is the difference between WaveRNN and dc_tts?
WaveRNN: WaveRNN Vocoder + TTS. dc_tts: A TensorFlow Implementation of DC-TTS. See the comparison table for live GitHub stats and shared categories.
When should I choose WaveRNN over dc_tts?
Choose WaveRNN over dc_tts when License: WaveRNN is MIT, dc_tts is Apache-2.0; Requirements: Python version must be equal to or higher than 3.6; Pytorch 1 with CUDA support is a prerequisite; Tags unique to WaveRNN: neural-vocoder, pytorch, speech-synthesis, tacotron; When you require a compact and efficient method to produce natural-sounding speech synthesis, specifically with the need for high fidelity in audio quality.
When should I choose dc_tts over WaveRNN?
Choose dc_tts over WaveRNN when License: dc_tts is Apache-2.0, WaveRNN 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 avoid WaveRNN?
Avoid using when you need extensive customization of the vocoder parameters, since it is optimized for specific configurations and might not offer the level of tweakability other frameworks provide. Not recommended if your setup does not support CUDA, as WaveRNN requires PyTorch with CUDA for execution.
When should I avoid dc_tts?
Last GitHub push was Apr 14, 2023 (dormant maintenance). Validate activity before betting a new project on dc_tts.
Is WaveRNN or dc_tts more popular on GitHub?
WaveRNN has more GitHub stars (2,191 vs 1,159). Stars measure visibility, not whether either tool fits your constraints.
Are WaveRNN and dc_tts open source?
Yes - both are open-source projects on GitHub (WaveRNN: MIT, dc_tts: Apache-2.0).
Where can I find alternatives to WaveRNN or dc_tts?
GraphCanon lists graph-backed alternatives at WaveRNN alternatives and dc_tts alternatives (WaveRNN markdown twin, dc_tts 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, WaveRNN or dc_tts?
WaveRNN: Dormant. dc_tts: 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 WaveRNN and dc_tts?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: WaveRNN trust report; dc_tts trust report.

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