From 864b6b3a43c821ed5eb5678169d73fadb091eb67 Mon Sep 17 00:00:00 2001 From: tanel <alumae@gmail.com> Date: Thu, 29 Jan 2015 16:34:00 +0200 Subject: [PATCH] Implemented optional rescoring with (large) a 'constant ARPA' LM --- README.md | 16 +++++++++++----- 1 file changed, 11 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index b8cb8c9..5e564b0 100644 --- a/README.md +++ b/README.md @@ -4,12 +4,18 @@ GStreamer plugin that wraps Kaldi's SingleUtteranceNnet2Decoder. It requires iVector-adapted DNN acoustic models. The iVectors are adapted to the current audio stream automatically. -~~The iVectors are reset after the decoding session (stream) ends. -Currently, it's not possible to save the adaptation state and recall it later -for a particular speaker, to make the adaptation persistent over multiple decoding -sessions.~~ -Update: the plugin saves the adaptation state between silence-segmented utterances and between +# CHANGELOG + +2015-01-09: Added language model rescoring functionality. In order to use it, +you have to specify two properties: `lm-fst` and `big-lm-const-arpa`. The `lm-fst` +property gives the location of the *original* LM (the one that was used fpr +compiling the HCLG.fst used during decodong). The `big-lm-const-arpa` property +gives the location of the big LM used that is used to rescore the final lattices. +The big LM must be in the 'ConstArpaLm' format, use the Kaldi's +`utils/build_const_arpa_lm.sh` script to produce it from the ARPA format. + +2014-11-11: the plugin saves the adaptation state between silence-segmented utterances and between multiple decoding sessions of the same plugin instance. That is, if you start decoding a new stream, the adaptation state of the previous stream is used (unless it's the first stream, in which case a global mean is used). -- GitLab