2.0.1

• Available as Docker image alumae/kiirkirjutaja:2.0.1 and alumae/kiirkirjutaja:latest
• Fixed an issue which caused words at sentence ends not to be recognizer correctly in some cases

2.0

• Available as Docker image alumae/kiirkirjutaja:2.0 and alumae/kiirkirjutaja:latest
• Now uses end-to-end streaming transducer models trained using Icefall.
• The new ASR model includes punctuation restoration, i.e., punctuation symbols are automatically inserted to the recognized stream of words
• Should provide 30% less ASR errors and much improved punctuation accuracy
• Docker image size reduced to from ~14 GB to 3.2 GB, as we don't need Kaldi and several other things any more

0.3.0

• Fixed a bug in Youtube presenter that caused timings to be sometimes messed up.
• Introduced a new command line argument --word-output-delay <seconds> that can be used to set a minimum time between a word
  occurring in speech and word appearing in subtitles. Recommended value is smth like 5. This makes word-by-word output
  timing more consistent and makes reading more comfortable. Otherwise, words in utterance ends can be displayed all very 'abruptly'.

Available as Docker image alumae/kiirkirjutaja:0.3.0 and alumae/kiirkirjutaja:latest. We had to migrate to Docker's native image repository since Koodivaramu doesn't allow to host Docker images any more.

0.2.8

• Updated Dockerfile to use latest Kaldi and a newer Pytorch

0.2.7

• At user's request, removed the automatic issuing of START command from FabBcastWordByWordPresenter

0.2.5

• Fixed a memory leak that caused memory usage to slowly increase
• Increased robustness in cases when FAB/Youtube API endpoint is down or not responding

Available as Docker image: koodivaramu.eesti.ee:5050/taltechnlp/kiirkirjutaja:0.2.5 and koodivaramu.eesti.ee:5050/taltechnlp/kiirkirjutaja:latest

0.2.4

Implemented presenter for FAB Live BCAST.
Activate with command line argument --fab-bcast-url, e.g. --fab-bcast-url http://localhost:8001/livetranscription

0.2.3

Increased robustness of the language ID module: is a non-target (i.e., not Estonian) language is detected at the 3 second mark, another check is done after 5 seconds. This is to filter out some false negatives when the utterance starts with some some hesitation sounds or otherwise non-standard words that sometimes confuse the language ID module.