Update README.md

README.md

@@ -135,6 +135,16 @@ This script starts a full ASR experiment and performs training, validation, forw
 
 **Note that you can stop the experiment at any time.** If you run again the script it will automatically start from the last chunk correctly processed. The training could take a couple of hours, depending on the available GPU.
 
+**Debug:** If you run into some errors, we suggest to do the following checks:
+1.	Take a look into the standard output.
+2.	If it is not helpful, take a look into the log.log file.
+3.	If the error is still not clear, run:
+```
+python run_nn.py exp/TIMIT_MLP_basic/exp_files/train_TIMIT_tr_ep000_ck00.cfg
+```
+In this way you “manually” run the training of the first chunk of speech an you can see all the errors directly from the standard output.
+
+
 8. At the end of training, the phone error rate (PER\%) is appended into the res.res file. To see more details on the decoding results, you can go into “decoding_test” in the output folder and take a look to the various files created.  For this specific example, we obtained the following *res.res* file:
 
 
@@ -245,6 +255,7 @@ steps/lmrescore_const_arpa.sh  $data_dir/lang_test_{tgsmall,fglarge} \
           $data_dir/test_clean $dec_dir $out_dir/decode_test_clean_fglarge   || exit 1;
 ```
 The final results obtaineed using rescoring (*fglarge*) are reported in the following table:
+
 | Model  | WER% |  
 | ------ | -----| 
 |  MLP  |  6.5 |