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From: E <oth...@ao...> - 2013-10-17 07:26:35
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Hello, I have been playing with Kaldi online recognizers (great work!) and wanted to ask if the FST approach is useful if I'm running under memory constraints. If I use traditional ARPA language model + acoustic models; total size of models is < 100 Mb (for 20,000 vocab size). But the HCLG.fst takes a whooping 500 Mbs! Why is this so (Perhaps I should read the papers to find the answers, but in short why size of HCLG.fst >> sum of size of individual *.fsts)? Is there some redundancy involved? What might be alternatives if one want to further reduce the size of HCLG.fst? Thanks. |