Julius Speech Recognition Engine 3.5.3

Julius is a high-performance, two-pass large vocabulary continuous speech recognition (LVCSR) decoder software for speech-related researchers and developers. Based on word 3-gram and context-dependent HMM, it can perform almost real-time decoding on most current PCs in 20k word dictation task.
Major search techniques are fully incorporated such as tree lexicon, N-gram factoring, cross-word context dependency handling, enveloped beam search, Gaussian pruning, Gaussian selection, etc. Besides search efficiency, it is also modularized carefully to be independent from model structures, and various HMM types are supported such as shared-state triphones and tied-mixture models, with any number of mixtures, states, or phones.
Standard formats are adopted to cope with other free modeling toolkit. The main platform is Linux and other Unix workstations, and also works on Windows. Julius is distributed with open license together with source codes, and has been used by many researchers and developers in Japan.
Main features:
- An open-source software (see terms and conditions of license (Japanese and English translation)).
- Real-time hi-speed and accurate recognition based on 2-pass strategy.
- Low memory requirement: less than 32MBytes required for work area (<64MBytes for 20k-word dictationwith on-memory 3-gram LM).
- Language and unit-dependent: Any LM in ARPA standard format and AM in HTK ascii hmmdefs format can be used.
- Highly configurable: can set various search parameters. Also alternate decoding algorithm (1-best/word-pair approx., word trellis/word graph intermediates, etc.) can be chosen.
- Full source code documentation and manual in Engligh / Japanese.
Supported features:
- Live microphone and network input
- GMM-based input rejection
- Successive decoding, delimiting input by short pause
- N-best output
- Word graph output
- Forced alignment on word, phoneme, and state level
- Confidence scoring
- Server mode and control API
- Many search parameters for tuning its performance
- Character code convertion for output.
Enhancements:
- Acoustic computation is now 20-40% faster.
- New grammar tools were provided, including "slf2dfa", a toolkit for converting HTK slf to Julian dfa.
- An option to load an HTK Config file to set correct acoustic parameter configuration was provided.
- Acoustic parameter configuration can be embedded into the header of a binary HMM file.
- Preliminary support for live recognition using an acoustic model with energy normalization was implemented.