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| author |   B. Watson | 2020-10-13 06:23:59 +0200 |
|---|---|---|
| committer |   Willy Sudiarto Raharjo | 2020-10-17 04:39:16 +0200 |
| commit | 271207d33299dea068bf28cc2cf7747d0c137315 (patch) | |
| tree | ce27a2f56f2a5823fafe2e34f886c9cdca248aa9 /development/julius | |
| parent | 99722947e4cfb6efab99f353977e6fab6c7a904c (diff) | |
| download | slackbuilds-271207d33299dea068bf28cc2cf7747d0c137315.tar.gz | |
development/julius: Fix README.
Signed-off-by: B. Watson <yalhcru@gmail.com>
Signed-off-by: Willy Sudiarto Raharjo <willysr@slackbuilds.org>
Diffstat (limited to 'development/julius')
| -rw-r--r-- | development/julius/README | 25 |
1 files changed, 13 insertions, 12 deletions
diff --git a/development/julius/README b/development/julius/README index f7868b4a3f..a45341c751 100644 --- a/development/julius/README +++ b/development/julius/README @@ -1,12 +1,13 @@ -"Julius" is a high-performance, two-pass large vocabulary continuous speech -recognition (LVCSR) decoder software for speech-related researchers and -developers. Based on word N-gram and context-dependent HMM, it can perform -almost real-time decoding on most current PCs in 60k 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 such -as HTK, CMU-Cam SLM toolkit, etc. +"Julius" is a high-performance, two-pass large vocabulary continuous +speech recognition (LVCSR) decoder software for speech-related +researchers and developers. Based on word N-gram and context-dependent +HMM, it can perform almost real-time decoding on most current +PCs in 60k 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 such as +HTK, CMU-Cam SLM toolkit, etc. |