From a74183ddb4ab8383bfe214b3745eb8a0a99ee47a Mon Sep 17 00:00:00 2001 From: Determinant Date: Thu, 25 Jun 2015 12:56:45 +0800 Subject: let HTK I/O implementation be a single package --- htk_io/examples/tnet_preprocessing_example2.lua | 68 +++++++++++++++++++++++++ 1 file changed, 68 insertions(+) create mode 100644 htk_io/examples/tnet_preprocessing_example2.lua (limited to 'htk_io/examples/tnet_preprocessing_example2.lua') diff --git a/htk_io/examples/tnet_preprocessing_example2.lua b/htk_io/examples/tnet_preprocessing_example2.lua new file mode 100644 index 0000000..1215b23 --- /dev/null +++ b/htk_io/examples/tnet_preprocessing_example2.lua @@ -0,0 +1,68 @@ +require 'speech.init' +gconf = {cumat_type = nerv.CuMatrixFloat, + batch_size = 158} +param_repo = nerv.ParamRepo({"global_transf.nerv"}) + +sublayer_repo = nerv.LayerRepo( + { + ["nerv.BiasLayer"] = + { + blayer1 = {{bias = "bias1"}, {dim_in = {429}, dim_out = {429}}}, + blayer2 = {{bias = "bias2"}, {dim_in = {429}, dim_out = {429}}} + }, + ["nerv.WindowLayer"] = + { + wlayer1 = {{window = "window1"}, {dim_in = {429}, dim_out = {429}}}, + wlayer2 = {{window = "window2"}, {dim_in = {429}, dim_out = {429}}} + } + }, param_repo, gconf) + +layer_repo = nerv.LayerRepo( + { + ["nerv.DAGLayer"] = + { + main = {{}, { + dim_in = {429}, dim_out = {429}, + sub_layers = sublayer_repo, + connections = { + ["[1]"] = "blayer1[1]", + ["blayer1[1]"] = "wlayer1[1]", + ["wlayer1[1]"] = "blayer2[1]", + ["blayer2[1]"] = "wlayer2[1]", + ["wlayer2[1]"] = "[1]" + } + }} + } + }, param_repo, gconf) + +reader = nerv.TNetReader({}, + { + id = "main_scp", + scp_file = "/slfs1/users/mfy43/swb_ivec/train_bp.scp", + conf_file = "/slfs1/users/mfy43/swb_ivec/plp_0_d_a.conf", + frm_ext = 5, + mlfs = { + ref = { + file = "/slfs1/users/mfy43/swb_ivec/ref.mlf", + format = "map", + format_arg = "/slfs1/users/mfy43/swb_ivec/dict", + dir = "*/", + ext = "lab" + } + }, + global_transf = layer_repo:get_layer("main") + }) + +utter = reader:get_data() +-- print(utter.main_scp) +print(utter.ref) +-- cf2 = nerv.ChunkFile("feat_256", "r") +-- input = cf2:read_chunk("input", gconf) + +-- for i = 0, 157 - 10 do +-- row_diff = input.trans[i] - utter.main_scp[i] +-- for j = 0, row_diff:ncol() - 1 do +-- nerv.printf("%.8f ", row_diff[j]) +-- end +-- nerv.printf("\n") +-- end -- cgit v1.2.3