Comparison
hifi-gan vs dc_tts
Verdict
Pick hifi-gan if hiFi-GAN is optimized for generating high-fidelity speech efficiently and supports both training from scratch and fine-tuning with pretrained models; pick dc_tts if dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies.
Markdown twin · hifi-gan alternatives · dc_tts alternatives
GraphCanon updated 3w
Trust & integrity
| Signal | hifi-gan | dc_tts |
|---|---|---|
| Maintenance | Dormant (731d since push) As of 3w · github_public_v1 | Dormant (1203d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 3w · github_public_v1 | Not a fork · Personal account As of 3w · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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 |
Tagline
- hifi-gan
- Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
- dc_tts
- A TensorFlow Implementation of DC-TTS
Stars
- hifi-gan
- 2.4k
- dc_tts
- 1.2k
Forks
- hifi-gan
- 555
- dc_tts
- 360
Open issues
- hifi-gan
- 111
- dc_tts
- 68
Language
- hifi-gan
- Python
- dc_tts
- Python
Adopt for
- hifi-gan
- HiFi-GAN is optimized for generating high-fidelity speech efficiently and supports both training from scratch and fine-tuning with pretrained models.
- dc_tts
- dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies.
Persona
- hifi-gan
- -
- dc_tts
- -
Runtime
- hifi-gan
- -
- dc_tts
- -
License
- hifi-gan
- MIT
- dc_tts
- Apache-2.0
Last pushed
- hifi-gan
- Jul 27, 2024
- dc_tts
- Apr 14, 2023
Categories
- hifi-gan
- Speech & Audio
- dc_tts
- Speech & Audio
Trust and health
Days since push
- hifi-gan
- 731d
- dc_tts
- 1203d
Open issues (now)
- hifi-gan
- 111
- dc_tts
- 68
OSV dependency advisories
- hifi-gan
- Published findings
- dc_tts
- No lockfile (source not queried)
Full report
- hifi-gan
- Trust report
- dc_tts
- Trust report
Choose hifi-gan if…
- License: hifi-gan is MIT, dc_tts is Apache-2.0.
- Tags unique to hifi-gan: deep-learning, gan, hifi-gan, pytorch.
- When you require real-time generation capabilities up to 167.9 times faster than real time on a single V100 GPU, or even 13.4 times faster on CPU than real time for the small footprint version
When NOT to use hifi-gan
- If your application prioritizes sample quality above speed, despite the competitive position of HiFi-GAN in both criteria
- When the computational resources for running models on a V100 GPU or leveraging the small footprint version's CPU efficiency are not available
- In scenarios requiring more than just high-fidelity speech synthesis but also complex text-to-speech natural language processing capabilities
Choose dc_tts if…
- License: dc_tts is Apache-2.0, hifi-gan 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 1229 days ago (dormant maintenance, Apr 14, 2023). Validate activity before betting a new project on dc_tts.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (jik876/hifi-gan) · observed Jul 29, 2026
- GitHub forks (jik876/hifi-gan) · observed Jul 29, 2026
- Last push (jik876/hifi-gan) · observed Jul 27, 2024
- License file (MIT) · observed Jul 29, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Kyubyong/dc_tts) · observed Jul 30, 2026
- GitHub forks (Kyubyong/dc_tts) · observed Jul 30, 2026
- Last push (Kyubyong/dc_tts) · observed Apr 14, 2023
- License file (Apache-2.0) · observed Jul 30, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: hifi-gan 2.4k · dc_tts 1.2k (synced Jul 29, 2026).
Common questions
- What is the difference between hifi-gan and dc_tts?
- hifi-gan: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis. dc_tts: A TensorFlow Implementation of DC-TTS. See the comparison table for live GitHub stats and shared categories.
- When should I choose hifi-gan over dc_tts?
- Choose hifi-gan over dc_tts when License: hifi-gan is MIT, dc_tts is Apache-2.0; Tags unique to hifi-gan: deep-learning, gan, hifi-gan, pytorch; When you require real-time generation capabilities up to 167.9 times faster than real time on a single V100 GPU, or even 13.4 times faster on CPU than real time for the small footprint version.
- When should I choose dc_tts over hifi-gan?
- Choose dc_tts over hifi-gan when License: dc_tts is Apache-2.0, hifi-gan 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 hifi-gan?
- If your application prioritizes sample quality above speed, despite the competitive position of HiFi-GAN in both criteria When the computational resources for running models on a V100 GPU or leveraging the small footprint version's CPU efficiency are not available In scenarios requiring more than just high-fidelity speech synthesis but also complex text-to-speech natural language processing capabilities
- 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.
- Is hifi-gan or dc_tts more popular on GitHub?
- hifi-gan has more GitHub stars (2,363 vs 1,156). Stars measure visibility, not whether either tool fits your constraints.
- Are hifi-gan and dc_tts open source?
- Yes - both are open-source projects on GitHub (hifi-gan: MIT, dc_tts: Apache-2.0).
- Where can I find alternatives to hifi-gan or dc_tts?
- GraphCanon lists graph-backed alternatives at hifi-gan alternatives and dc_tts alternatives (hifi-gan 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, hifi-gan or dc_tts?
- hifi-gan: 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 hifi-gan and dc_tts?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: hifi-gan trust report; dc_tts trust report.