All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog.
Date is year-month-day format.
Changes:
- Fix model download bug due to change in Flask
Changes:
- Updated dependencies, including Python version, Transformers, PyTorch, most packages.
- Minor changes to HFT model class in response to Transformers Trainer update.
Added feature that allows:
- locally downloading models trained using Elpis.
- downloading fine-tuned or pre-trained models from HuggingFace which can then be further fine-tuned on particular user datasets.
- uploading trained models for the purposes of performing transcription.
Changes:
- Changed training dashboard layout.
- Show engine type for models when choosing models for transcription.
Documentation updates:
- Added documentation regarding starting a GCP account, billing, APIs and quotas setup.
- Cleaning up of existing documentation.
- Fixed logging error caused by a Kaldi training stage failing.
- Fixed white screen of death when uploading a single wav to datasets
- Fixed HFT failing on first transcription due to it expecting audio.wav name
- Fixed
yarn watch
for devs
- Resampling utility
- Reformat all Python code using Black formatter
- Clean-up of Dockerfile
- Caching of port-audio for Kaldi build
- Clean-up protobuf install in Dockerfile
- Delete buttons for datasets, pron dicts and models
- Minor bug fixes
- 44.1kHz sample rate to 16kHz
- Huggingface Transformers wav2vec2 engine
- Fixed CLI examples
- ESPnet engine
- Automated docker builds on releases (vX.Y.Z) and pushes to master (latest)
- Change ports from 5000 to 5001 to avoid conflict with greedy MacOS Airplay speaker thing
- Show Kaldi hypothesis confidence on the transcription page
- Updated pympi, praatio, llvm, librosa, numba versions
- Front end and dynamic i18n support
- Minor gui tweaks
- New flow for GUI welcome and engine select
- Start implementing feedback from UX study
- Show train logs in GUI. Kaldi is split into stages, ESPnet is single stage.
- Add DEV_MODE setting for GUI
- Pin ESPnet to CoEDL fork of persephone-tools/espnet
- Changed to use pyenv for Python version management
- Voice Activity Detection
- Bring GUI Dockerfile into line with with CPU version
- Modify Elpis to use Poetry for dependency management
- Dockerfile to use Python 3.8 as default for Elpis
- Monorepo: brought https://github.com/coedl/elpis-gui into this repo under elpis/gui
- Significant restructure: moved gpu and examples under /elpis
- Updated Docker image to an Ubuntu 20.04 base image
- Dockerfile to use Python 3.7 as default for Elpis
- Rearranged Dockerfile to group like things and install ESPne earlier
- ESPnet
- Fixed changelog date for docs
- Docs
- Separated log files into individual logs for each stage while processing, and build complete log when done
- Fixed annotations not resetting when changing tier settings
- Moved CLI example into a Kaldi dir
- Fixed Kaldi Elan CLI example, now links dataset and pronunciation dictionary independently