trunk,nnet1: updating the 'usage' messages in some nnet1 tools

git-svn-id: https://svn.code.sf.net/p/kaldi/code/trunk@5169 5e6a8d80-dfce-4ca6-a32a-6e07a63d50c8

src/nnetbin/feat-to-post.cc

@@ -28,7 +28,8 @@ int main(int argc, char *argv[]) {
   typedef kaldi::int32 int32;
   try {
     const char *usage =
-        "Convert features into posterior format, is used as NN training targets (Karel's nnet1).\n"
+        "Convert features into posterior format, which is used for NN training targets\n"
+        "in Karel's nnet1 tools.\n"
         "(speed is not an issue for reasonably low NN-output dimensions)\n"
         "Usage:  feat-to-post [options] feat-rspecifier posteriors-wspecifier\n"
         "e.g.:\n"

src/nnetbin/nnet-info.cc

@@ -28,8 +28,8 @@ int main(int argc, char *argv[]) {
     typedef kaldi::int32 int32;
 
     const char *usage =
-        "Print human-readable information about the neural network\n"
-        "acoustic model to the standard output\n"
+        "Print human-readable information about the neural network.\n"
+        "(topology, various weight statistics, etc.) It prints to stdout.\n"
         "Usage:  nnet-info [options] <nnet-in>\n"
         "e.g.:\n"
         " nnet-info 1.nnet\n";

src/nnetbin/nnet-initialize.cc

@@ -28,10 +28,10 @@ int main(int argc, char *argv[]) {
     typedef kaldi::int32 int32;
 
     const char *usage =
-        "Copy Neural Network model (and possibly change binary/text format)\n"
-        "Usage:  nnet-initialize [options] <nnet-config-in> <nnet-out>\n"
+        "Initialize Neural Network parameters according to a prototype.\n"
+        "Usage:  nnet-initialize [options] <nnet-prototype-in> <nnet-out>\n"
         "e.g.:\n"
-        " nnet-copy --binary=false nnet.conf nnet.init\n";
+        " nnet-initialize --binary=false nnet.proto nnet.init\n";
 
     SetVerboseLevel(1); // be verbose by default
 

src/nnetbin/nnet-train-lstm-streams.cc

@@ -38,7 +38,7 @@ int main(int argc, char *argv[]) {
     const char *usage =
         "Perform one iteration of LSTM training by Stochastic Gradient Descent.\n"
         "This version use pdf-posterior as targets, prepared typically by ali-to-post.\n"
-        "The updates are done per-utternace, shuffling options are dummy for compatibility reason.\n"
+        "The updates are done per-utterance, shuffling options are dummy for compatibility reason.\n"
         "\n"
         "Usage:  bd-nnet-train-lstm-streams [options] <feature-rspecifier> <targets-rspecifier> <model-in> [<model-out>]\n"
         "e.g.: \n"

src/nnetbin/nnet-train-perutt.cc

@@ -33,7 +33,7 @@ int main(int argc, char *argv[]) {
     const char *usage =
         "Perform one iteration of Neural Network training by Stochastic Gradient Descent.\n"
         "This version use pdf-posterior as targets, prepared typically by ali-to-post.\n"
-        "The updates are done per-utternace, shuffling options are dummy for compatibility reason.\n"
+        "The updates are done per-utterance, shuffling options are dummy for compatibility reason.\n"
         "\n"
         "Usage:  nnet-train-perutt [options] <feature-rspecifier> <targets-rspecifier> <model-in> [<model-out>]\n"
         "e.g.: \n"

src/nnetbin/paste-post.cc

@@ -35,17 +35,18 @@ int main(int argc, char *argv[]) {
   typedef kaldi::int32 int32;
   try {
     const char *usage =
-        "Combine 2 or more streams with NN-training targets into single stream.\n"
+        "Combine 2 or more `posterior-streams` with NN-training targets into a single stream.\n"
         "As the posterior streams are pasted, the output dimension is the sum\n"
-        "of the input dimensions. This is used when training NN with\n"
-        "multiple softmaxes on its output. This is used in multi-task, \n"
-        "multi-lingual or multi-database training. Depending on the context,\n"
-        "an utterance is not required to be in all the input streams.\n"
-        "For a multi-database training only 1 output layer will be active.\n"
+        "of the input dimensions. This tool is used when training NN with multiple\n"
+        "softmaxes on output, which is needed in multi-task, multi-lingual\n"
+        "or multi-database training.\n"
+        "\n"
+        "With '--allow-partial=true' an utterance-key is not required to be\n"
+        "present in all of the input streams.\n"
         "\n"
         "The lengths of utterances are provided as 1st argument.\n"
         "The dimensions of input stream are set as 2nd in argument.\n"
-        "Follow the input and output streams which are in 'posterior' format.\n"
+        "The following arguments are the input and output streams in 'posterior' format.\n"
         "\n"
         "Usage: paste-post <featlen-rspecifier> <dims-csl> <post1-rspecifier> ... <postN-rspecifier> <post-wspecifier>\n"
         "e.g.:\n"

src/nnetbin/rbm-train-cd1-frmshuff.cc

@@ -57,7 +57,7 @@ int main(int argc, char *argv[]) {
     int32 num_iters = 1; 
     po.Register("num-iters", &num_iters, 
                 "Number of iterations (smaller datasets should have more iterations, "
-                "iterating within tool becase of linear momentum scheduling)");
+                "iterating within tool because of linear momentum scheduling)");
 
     std::string feature_transform;
     po.Register("feature-transform", &feature_transform, "Feature transform in Nnet format");