ESPnet vs SpeechRecognition
ESPnet
espnet.github.ioSpeechRecognition
github.comSide by side
| Figure | ESPnet | SpeechRecognition |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | Yes | — |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 1 |
| Spec score · Speech Recognition Software | 8.8 (#9) | 7.6 (#25) |
| Founded | 2018 | 2014 |
| Installation | The installation guide documents editable pip installation and optional dependency groups for tasks such as ASR, TTS, and speech enhancement. | The README gives `pip install SpeechRecognition` as the easiest installation method and also describes installing from the PyPI source distribution. |
| License | The project homepage states that ESPnet is released under the Apache License 2.0. | The library is available under the 3-clause BSD license; included FLAC binaries are GPLv2-licensed. |
| Purpose | ESPnet is an end-to-end speech processing toolkit for speech recognition, text-to-speech, speech translation, speech enhancement, speaker diarization, spoken language understanding, and more. | SpeechRecognition is a Python library for speech recognition with support for several engines and APIs, online and offline. |
Plans
In their own words
ESPnet
ESPnet is an open-source toolkit for speech processing, including recognition, text-to-speech, translation, enhancement, speaker diarization, and spoken language understanding. It provides complete recipes for a range of tasks, plus tutorials, notebooks, and demos for existing models. Users can install ESPnet and espnet-model-zoo with pip to run inference on existing models; published models can also run in CPU or GPU inference containers without checking out the repository. Installation supports editable pip setup and optional dependency groups for tasks such as ASR, TTS, and speech enhancement. Training requires a separate extra that includes Lightning, TensorBoard, W&B, torch_optimizer, matplotlib, and Dask. Some task-specific packages must also be installed separately when a recipe needs them. ESPnet 1 is no longer supported, while ESPnet2 users can skip installing Kaldi. The toolkit is released under Apache License 2.0 and permits commercial use. It offers API access and lists Linux, macOS, Windows, and self-hosted platforms; WAV is the listed export format.
SpeechRecognition
SpeechRecognition has no write-up on Specifiction yet; its figures are above.