LM scaling is intended to control the ratio between the LM strength and
the acoustic model strength *after* decoding, when the best path in the
lattice is generated.
Setting this to a value higher than 1.0 (default) makes the LM more
prominent in the lattice path weighting, so the best path may be more
aligned with the LM, and not with the acoustic model.

Signed-off-by: Amit Beka <amit.beka@gmail.com>

When decoding the input, the output lattice is scaled using the acoustic
scale parameter. When 'inverse-scale' is set to TRUE, the lattice is
re-scaled back (inverse the acoustic scale) before the hypothesis is
extracted.

This behavior is common when playing with different scales after the
decoding phase.

Signed-off-by: Amit Beka <amit.beka@gmail.com>

Fix for adaptation state being get_property() is called soon after initialization (https://github.com/alumae/gst-kaldi-nnet2-online/issues/1)