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AHTD3A0002_Para2_1-1 | 83.26607 | -5840.735 | 5757.46893 | |
AHTD3A0002_Para2_1-2 | 88.04139 | -5841.306 | 5753.26461 | |
AHTD3A0002_Para2_1-3 | 84.77756 | -5837.759 | 5752.98144 | |
AHTD3A0002_Para2_1-4 | 87.3546 | -5839.219 | 5751.8644 |
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It is possible to obtain posterior probabilities for each of the n-best sentences. If you use nbest-to-linear you can get the lm-cost and the acoustic cost for each nbest. If you scale down the acoustics, negate both of the costs to get logprobs, add the lm and acoustic costs and exponentiate, you'll get an unnormalized probability for each element of the n-best list. You could normalize those to sum to one. [of course, you'd compute this differently to avoid overflow in the exp.]
On Sat, Nov 19, 2016 at 12:47 PM, Sana Khamekhem <sana.kh...@gmail.com> wrote:
Hi,I'm planning to extract n best hypothesis of utterances, and to get the confidence score for each one (per sentence and not per word),utt_1-1 1 0.2 0.1 waAkeAdhAlaAkeA toAaaAfaAraA.... score1utt_1-2 1 0.2 0.1 .. .... score2
utt_1-3 1 0.2 0.1 .. Hi .... score3
...Is there a way to do this??Now, I'im using this script to get nbest without scores:gunzip -c $dir/lat.1.gz |\lattice-to-nbest --acoustic-scale=0.0883 --n=10 --lm-scale=1.0 ark:- ark:- | \nbest-to-ctm --precision=4 ark:- - | utils/int2sym.pl -f 5 $lang/words.txt > $dir/NBest.10.ctm || exit 1;
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gunzip -c $decode_dir/lat.1.gz |\
src/latbin/lattice-to-nbest --acoustic-scale=0.1 --n=10 ark:- ark:- |\
src/latbin/nbest-to-linear ark:- ark,t:$decode_dir/NBest_10/ali.1 ark,t:$decode_dir/NBest_10/tra.1 ark,t:$decode_dir/NBest_10/lmcost.1 ark,t:$decode_dir/NBest_10/accost.1
For demonstration I've created a .csv file:
utt_id,rank,accost,lmcost,(0.1*accost-lmcost)
2000_bos_7000,1,-3663.002,138.4283,-504.72850000000005
2000_bos_7000,2,-3688.515,141.0154,-509.8669
2000_bos_7000,3,-3641.403,136.6397,-500.78
2000_bos_7000,4,-3666.916,139.2268,-505.9184
2000_bos_7000,5,-3687.323,141.3045,-510.03679999999997
2000_bos_7000,6,-3665.723,139.5159,-506.0882
2000_bos_7000,7,-3639.544,137.5812,-501.53559999999993
2000_bos_7000,8,-3665.056,140.1684,-506.674
2000_bos_7000,9,-3676.495,141.3441,-508.9936
2000_bos_7000,10,-3702.008,143.9312,-514.132
Questions:
Hello,I'm also trying to obtain the nbest hypotheses for the purpose of lm-rescoring but I'm having some confusion on the posterior logprobs so I've been following this post. I used the following commands to generate the lm and acoustic costs (logprobs) and corresponding output:gunzip -c $decode_dir/lat.1.gz |\
src/latbin/lattice-to-nbest --acoustic-scale=0.1 --n=10 ark:- ark:- |\
src/latbin/nbest-to-linear ark:- ark,t:$decode_dir/NBest_10/ali.1 ark,t:$decode_dir/NBest_10/tra.1 ark,t:$decode_dir/NBest_10/lmcost.1 ark,t:$decode_dir/NBest_10/accost.1
For demonstration I've created a .csv file:
utt_id,rank,accost,lmcost,(0.1*accost-lmcost)
2000_bos_7000,1,-3663.002,138.4283,-504.72850000000005
2000_bos_7000,2,-3688.515,141.0154,-509.8669
2000_bos_7000,3,-3641.403,136.6397,-500.78
2000_bos_7000,4,-3666.916,139.2268,-505.9184
2000_bos_7000,5,-3687.323,141.3045,-510.03679999999997
2000_bos_7000,6,-3665.723,139.5159,-506.0882
2000_bos_7000,7,-3639.544,137.5812,-501.53559999999993
2000_bos_7000,8,-3665.056,140.1684,-506.674
2000_bos_7000,9,-3676.495,141.3441,-508.9936
2000_bos_7000,10,-3702.008,143.9312,-514.132
Questions:
- If accost and lmcost are both logprobs, is there any reason why accost is negative and and lmcost is positive? I negated lmcost accordingly, assuming that the printed format was the -logprob (from another post).
- More importantly, I expected the posterior logprobs (0.1*accost-lmcost) to be sorted in descending order with the nbest ranks. Why isn't this the case?
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Utterance | LM Cost | Accost |
som01_015a2dcf-2f74-48f1-9e75-827599719854_AudioAttachment-1 | 24.03416 | 1884.988 |
som01_015a2dcf-2f74-48f1-9e75-827599719854_AudioAttachment-2 | 34.41694 | 1874.884 |
som01_015a2dcf-2f74-48f1-9e75-827599719854_AudioAttachment-3 | 28.41609 | 1881.671 |
som01_015a2dcf-2f74-48f1-9e75-827599719854_AudioAttachment-4 | 38.07364 | 1872.384 |
som01_015a2dcf-2f74-48f1-9e75-827599719854_AudioAttachment-5 | 30.7676 | 1879.962 |
som01_015a2dcf-2f74-48f1-9e75-827599719854_AudioAttachment-6 | 34.76073 | 1876.355 |
Yes
On Thu, May 7, 2020 at 7:36 PM Naveen Gabriel <naveen...@gmail.com> wrote:
I had read jurafsy book where it mentioned that the language model is scaled up.So should assume that the effect is same when acoustic model is scaled down ?
On Thu, May 7, 2020 at 7:14 AM Daniel Povey <dpo...@gmail.com> wrote:
Read the HTK Book, that might help. It's about the modeling assumptions not being right (HMM assumes no correlations given HMM state, but actually they are correlated).
On Wed, May 6, 2020 at 10:55 PM Naveen Gabriel <naveen...@gmail.com> wrote:
Hi Dan--The scaling down of acoustic model. I was wondering why it is required.
On Saturday, November 19, 2016 at 6:47:02 PM UTC+1, Sana Khamekhem wrote:Hi,I'm planning to extract n best hypothesis of utterances, and to get the confidence score for each one (per sentence and not per word),utt_1-1 1 0.2 0.1 waAkeAdhAlaAkeA toAaaAfaAraA.... score1utt_1-2 1 0.2 0.1 .. .... score2utt_1-3 1 0.2 0.1 .. .... score3...Is there a way to do this??Now, I'im using this script to get nbest without scores:gunzip -c $dir/lat.1.gz |\lattice-to-nbest --acoustic-scale=0.0883 --n=10 --lm-scale=1.0 ark:- ark:- | \nbest-to-ctm --precision=4 ark:- - | utils/int2sym.pl -f 5 $lang/words.txt > $dir/NBest.10.ctm || exit 1;
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Yes
On Thu, May 7, 2020 at 7:36 PM Naveen Gabriel <naveen...@gmail.com> wrote:
I had read jurafsy book where it mentioned that the language model is scaled up.So should assume that the effect is same when acoustic model is scaled down ?
On Thu, May 7, 2020 at 7:14 AM Daniel Povey <dpo...@gmail.com> wrote:
Read the HTK Book, that might help. It's about the modeling assumptions not being right (HMM assumes no correlations given HMM state, but actually they are correlated).
On Wed, May 6, 2020 at 10:55 PM Naveen Gabriel <naveen...@gmail.com> wrote:
Hi Dan--The scaling down of acoustic model. I was wondering why it is required.
On Saturday, November 19, 2016 at 6:47:02 PM UTC+1, Sana Khamekhem wrote:Hi,I'm planning to extract n best hypothesis of utterances, and to get the confidence score for each one (per sentence and not per word),utt_1-1 1 0.2 0.1 waAkeAdhAlaAkeA toAaaAfaAraA.... score1utt_1-2 1 0.2 0.1 .. .... score2utt_1-3 1 0.2 0.1 .. .... score3...Is there a way to do this??Now, I'im using this script to get nbest without scores:gunzip -c $dir/lat.1.gz |\lattice-to-nbest --acoustic-scale=0.0883 --n=10 --lm-scale=1.0 ark:- ark:- | \nbest-to-ctm --precision=4 ark:- - | utils/int2sym.pl -f 5 $lang/words.txt > $dir/NBest.10.ctm || exit 1;
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