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nerv.speech_utils = {}
function nerv.speech_utils.global_transf(feat_utter, global_transf, frm_ext, gconf)
local step = frm_ext * 2 + 1
-- expand the feature
local expanded = gconf.cumat_type(feat_utter:nrow(), feat_utter:ncol() * step)
expanded:expand_frm(gconf.cumat_type.new_from_host(feat_utter), frm_ext)
-- rearrange the feature (``transpose'' operation in TNet)
local rearranged = expanded:create()
rearranged:rearrange_frm(expanded, step)
-- prepare for transf
local input = {rearranged}
local output = {rearranged:create()}
-- do transf
global_transf:init(input[1]:nrow())
global_transf:propagate(input, output)
-- trim frames
expanded = gconf.mmat_type(output[1]:nrow() - frm_ext * 2, output[1]:ncol())
output[1]:copy_toh(expanded, frm_ext, feat_utter:nrow() - frm_ext)
collectgarbage("collect")
return expanded
end
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