Closed madhavsund closed 8 years ago
I am also interested to know, since in your case there is (almost) no language model's effect, I would suggest a bigger acwt.
both max-active(5000 by default) and beam (17 by default) can be smaller. But anyway, to tune them on you own test set would be the best way.
Please let me know if I am wrong.
Best
You can create a fake language model where each word (digit) has the probability of 1/10. Then the optimal acoustic weight will approximate what we normally use
Can you please further explain that by saying optimal aw, you mean 0.6 in the latgen-faster? If I understand correctly, in the latgen-faster, acoustic_scale is only used after the lattice is generated (for applying fst::scaleLattice()). But why the acoustic_scale is not used in the decode() and GetRawLattice()?
Thank you very much
Best
If you check https://github.com/srvk/eesen/blob/master/src/decoderbin/latgen-faster.cc, you can see that acoustic_scale is truly used in lattice generation
what would be the optimal values for decoding the digit corpus having only 10 words --beam , --lattice_beam, --max-active, --acwt
any thumb rule i.e vocabulary size vs these parameters