Gmail Backup is still online

Jan Švec and I wrote Gmail Backup back in 2008 — a one-click tool that pulled your Gmail down over IMAP into a local folder, with incremental backups so you only fetched what was new. It ran on Windows and Linux, the code went out under GPL v3, and for a few years it was the answer people gave when someone asked how to get their mail off Google's servers.

It is old software and the world has moved on, but the site is still up: www.gmail-backup.com, with the downloads, the documentation, the FAQ and the forum threads intact. I recently moved the whole thing to static hosting and put it back on HTTPS, which is the only reason it still loads at all.

Worth remembering the premise, which has not aged: your mail is only yours if you have a copy of it.

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Viterbi Algorithm in C++ and using STL

To practice my C++ and STL skills, I implemented the Viterbi algorithm example from the Wikipedia page: http://en.wikipedia.org/wiki/Viterbi_algorithm . The original algorithm was implemented in Python. I reimplemented the example in C++ and I used STL (mainly vector and map classes). This code is in public-domain. So, use it as you want. The complete solution for MS Visual C++ 2008 can be found at http://filip.jurcicek.googlepages.com/ViterbiSTL.rar // ViterbiSTL.cpp : is an C++ and STL implementatiton of the Wikipedia example // Wikipedia: http://en.wikipedia.org/wiki/Viterbi_algorithm#A_concrete_example // It as accurate implementation as it was possible #include "stdafx.h" #include "string" #include "vector" #include "map" #include "iostream" using namespace std; //states = ('Rainy', 'Sunny') // //observations = ('walk', 'shop', 'clean') // //start_probability = {'Rainy': 0.6...

how the make HCL and G graphs, and on the fly compositon of HCL and G for KALDI

Well, I had again to do something ;-) The task is to generate/create/update a decoding graph for KALDI on the fly. In my case, I aim at changing a G (grammar) in the context of a dialogue system. One can generate a new HCLG but this would take a lot of time as this involves FST determinization, epsilon-removal, minimization, etc. Therefore, I tried to use on-the-fly composition of statically prepared HCL and G. At first, I struggled with it but later I made it work. See https://github.com/jpuigcerver/kaldi-decoders/issues/1 Here is a short summary: At the end, I managed to get LabelLookAheadMatcher to work. It is mostly based on the code and examples in opendcd, e.g. https://github.com/opendcd/opendcd/blob/master/script/makegraphotf.sh . First, Here is how I build and prepare the HCL and G. Please not that OpenFST must be compiled with --enable-lookahead-fsts , see http://www.openfst.org/twiki/bin/view/FST/ReadMe . #--------------- fstdeterminize ${lang}/...

kaldi editing nnet3 chain model - adding a softmax layer on top of the chain output

I had to do one more thing: to edit a trained kaldi nnet3 chain model and add a softmax layer on top of the chain model. The reason for this is to get "probability" like output directly from the chain model First, let's look at the nnet structure: nnet3-am-info final.mdl input-dim: 20 ivector-dim: -1 num-pdfs: 6105 prior-dimension: 0 # Nnet info follows. left-context: 15 right-context: 15 num-parameters: 15499085 modulus: 1 input-node name=input dim=20 component-node name=L0_fixaffine component=L0_fixaffine input=Append(Offset(input, -1), input, Offset(input, 1)) input-dim=60 output-dim=60 component-node name=Tdnn_0_affine component=Tdnn_0_affine input=L0_fixaffine input-dim=60 output-dim=625 component-node name=Tdnn_0_relu component=Tdnn_0_relu input=Tdnn_0_affine input-dim=625 output-dim=625 component-node name=Tdnn_0_renorm component=Tdnn_0_renorm input=Tdnn_0_relu input-dim=625 output-dim=625 component-node name=Tdnn_1_affine component=Tdnn_1_affi...

Filip Jurčíček

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