Comparison
dc_tts vs TensorFlowASR
Verdict
Pick dc_tts if dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies; pick TensorFlowASR if tensorFlowASR is an advanced Automatic Speech Recognition library built on TensorFlow 2 that supports modern architectures such as Conformer and RNN-Transducer.
Markdown twin · dc_tts alternatives · TensorFlowASR alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | dc_tts | TensorFlowASR |
|---|---|---|
| Maintenance | Dormant (1203d since push) As of 3w · github_public_v1 | Very active (0d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 3w · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings 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
- dc_tts
- A TensorFlow Implementation of DC-TTS
- TensorFlowASR
- Almost State-of-the-art Automatic Speech Recognition in Tensorflow 2
Stars
- dc_tts
- 1.2k
- TensorFlowASR
- 1.0k
Forks
- dc_tts
- 360
- TensorFlowASR
- 239
Open issues
- dc_tts
- 68
- TensorFlowASR
- 47
Language
- dc_tts
- Python
- TensorFlowASR
- Python
Adopt for
- dc_tts
- dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies.
- TensorFlowASR
- TensorFlowASR is an advanced Automatic Speech Recognition library built on TensorFlow 2 that supports modern architectures such as Conformer and RNN-Transducer.
Persona
- dc_tts
- -
- TensorFlowASR
- -
Runtime
- dc_tts
- -
- TensorFlowASR
- -
License
- dc_tts
- Apache-2.0
- TensorFlowASR
- Apache-2.0
Last pushed
- dc_tts
- Apr 14, 2023
- TensorFlowASR
- Jul 30, 2026
Categories
- dc_tts
- Speech & Audio
- TensorFlowASR
- Speech & Audio
Trust and health
Maintenance
- dc_tts
- Dormant (18%)
- TensorFlowASR
- Very active (96%)
Days since push
- dc_tts
- 1203d
- TensorFlowASR
- 0d
Open issues (now)
- dc_tts
- 68
- TensorFlowASR
- 47
Owner type
- dc_tts
- User
- TensorFlowASR
- Organization
OSV dependency advisories
- dc_tts
- No lockfile (source not queried)
- TensorFlowASR
- Published findings
Full report
- dc_tts
- Trust report
- TensorFlowASR
- Trust report
Choose dc_tts if…
- 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, tts.
- 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 1228 days ago (dormant maintenance, Apr 14, 2023). Validate activity before betting a new project on dc_tts.
Choose TensorFlowASR if…
- Tags unique to TensorFlowASR: automatic-speech-recognition, conformer, contextnet, ctc.
- TensorFlowASR ships Docker support for self-hosted deployment.
- When focusing on state-of-the-art performance with models like Conformer or ContextNet, which are among its supported architectures and not necessarily included in all ASR libraries.
When NOT to use TensorFlowASR
- When Python version constraints are an issue, as TensorFlowASR strictly requires python >= 3.12 on Apple Silicon devices, limiting compatibility.
- If your project cannot accommodate the extra installation steps involving `ctc_decoders` and `rnnt_loss`, which implies additional complexity in setting up the environment.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- 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 (TensorSpeech/TensorFlowASR) · observed Jul 31, 2026
- GitHub forks (TensorSpeech/TensorFlowASR) · observed Jul 31, 2026
- Last push (TensorSpeech/TensorFlowASR) · observed Jul 30, 2026
- License file (Apache-2.0) · observed Jul 31, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: dc_tts 1.2k · TensorFlowASR 1.0k (synced Jul 30, 2026).
Common questions
- What is the difference between dc_tts and TensorFlowASR?
- dc_tts: A TensorFlow Implementation of DC-TTS. TensorFlowASR: Almost State-of-the-art Automatic Speech Recognition in Tensorflow 2. See the comparison table for live GitHub stats and shared categories.
- When should I choose dc_tts over TensorFlowASR?
- Choose dc_tts over TensorFlowASR when 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, tts; dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies. - When should I choose TensorFlowASR over dc_tts?
- Choose TensorFlowASR over dc_tts when Tags unique to TensorFlowASR: automatic-speech-recognition, conformer, contextnet, ctc; TensorFlowASR ships Docker support for self-hosted deployment; When focusing on state-of-the-art performance with models like Conformer or ContextNet, which are among its supported architectures and not necessarily included in all ASR libraries.
- When should I avoid dc_tts?
- Last GitHub push was 1228 days ago (dormant maintenance, Apr 14, 2023). Validate activity before betting a new project on dc_tts.
- When should I avoid TensorFlowASR?
- When Python version constraints are an issue, as TensorFlowASR strictly requires python >= 3.12 on Apple Silicon devices, limiting compatibility. If your project cannot accommodate the extra installation steps involving
ctc_decodersandrnnt_loss, which implies additional complexity in setting up the environment. - Is dc_tts or TensorFlowASR more popular on GitHub?
- dc_tts has more GitHub stars (1,156 vs 1,010). Stars measure visibility, not whether either tool fits your constraints.
- Are dc_tts and TensorFlowASR open source?
- Yes - both are open-source projects on GitHub (dc_tts: Apache-2.0, TensorFlowASR: Apache-2.0).
- Where can I find alternatives to dc_tts or TensorFlowASR?
- GraphCanon lists graph-backed alternatives at dc_tts alternatives and TensorFlowASR alternatives (dc_tts markdown twin, TensorFlowASR 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, dc_tts or TensorFlowASR?
- dc_tts: Dormant. TensorFlowASR: Very active. 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 TensorFlowASR?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: dc_tts trust report; TensorFlowASR trust report.