Hi,
It is unlikely that having 20 speakers have caused this problem. I expect that some data files are corrupted, i. e., failed to extract speech features from waveforms. Please check whether your data is OK or not.
Regards,
Heiga
Hi,Thank you for telling me this. Compared to the delta f0 of the speaker dependent model I trained previously, it is too big ( the current model I'm training is an average voice model ) . I thought it was because I used speech sentences of 20 speakers, which resulted in big delta f0. I used the same configuration and option settings of speaker dependent model training and replaced the training data with the data of 20 speakers. Is it correct to train a average voice model without modify any configuration and option?Regards,Jay2012/2/24 Keiichiro Oura <uratec@xxxxxxxxxxxxxxx>Hi,
It seems that delta lf0 is not trained correctly.
<VARIANCE> 1
2.078870e+12
The variance is too big.
You should check delta f0 sequence in training data.
Regards,
Keiichiro Oura
2012/2/24 li jay <lij.acd@xxxxxxxxx>:
> Hi,
>
> The following is the part of re_clustered.mmf
>
> 170535 ~p "lf0_s2_523-3"
> 170536 <STREAM> 3
> 170537 <NUMMIXES> 2
> 170538 <MIXTURE> 1 1.582146e-01
> 170539 <MEAN> 1
> 170540 -9.624681e-03
> 170541 <VARIANCE> 1
> 170542 2.078870e+12
> 170543 <GCONST> 3.020072e+01
> 170544 <MIXTURE> 2 8.417839e-01
> 170545 <MEAN> 0
> 170546 <VARIANCE> 0
> 170547 <GCONST> 0.000000e+00
> 170548 ~p "lf0_s2_523-4"
> 170549 <STREAM> 4
> 170550 <NUMMIXES> 2
> 170551 <MIXTURE> 1 1.582144e-01
> 170552 <MEAN> 1
> 170553 -1.753086e-03
> 170554 <VARIANCE> 1
> 170555 8.353170e-04
> 170556 <GCONST> -5.249823e+00
> 170557 <MIXTURE> 2 8.417841e-01
> ...
>
> 260387 ~h
> "CH_dz`-CH_U+sp/T:x_4_4_x_4/WS:1_6_6/CS:2_7_8/CW:2_1_2/PS:5_19_23/PW:5_1_5/PC:2_1_2"
> 260388 <BEGINHMM>
> 260389 <NUMSTATES> 7
> 260390 <STATE> 2
> 260391 <STREAM> 1
> 260392 ~p "mgc_s2_21"
> 260393 <STREAM> 2
> 260394 ~p "lf0_s2_523-2"
> 260395 <STREAM> 3
> 260396 ~p "lf0_s2_523-3"
> 260397 <STREAM> 4
> 260398 ~p "lf0_s2_523-4"
> 260399 <STATE> 3
> 260400 <STREAM> 1
> ...
>
> There seem to be no error or in the stream[3]. What could affect the
> building process of regression tree?
>
> Regards,
> Jay
>
> 2012/2/24 Keiichiro Oura <uratec@xxxxxxxxxxxxxxx>
>>
>> Hi,
>>
>> The distributions are in .../cmp/re_clustered.mmf
>>
>> Regards,
>> Keiichiro Oura
>>
>>
>> 2012/2/24 li jay <lij.acd@xxxxxxxxx>:
>> > Hi,
>> >
>> > The following is part of the log file when I tried to build the
>> > regression
>> > tree:
>> >
>> > Splitting Node 32763, score 9.997541e+09
>> > (Stream=3, vSize=1)
>> > Splitting Node 32765, score 9.997541e+09
>> > (Stream=3, vSize=1)
>> > Splitting Node 32767, score 9.997541e+09
>> > (Stream=3, vSize=1)
>> > Splitting Node -32767, score 9.997541e+09
>> > (Stream=3, vSize=1)
>> > Splitting Node -32765, score 9.997541e+09
>> > (Stream=3, vSize=1)
>> > Splitting Node -32763, score 9.997541e+09
>> >
>> > The reason why the index went to negative value seemed to be an
>> > overflow occurred.
>> > Could you tell me in which file I can check the distribution of
>> > stream[3]?
>> > Thank you for you help.
>> >
>> > Regards,
>> > Jay
>> >
>> > 2012/2/23 Keiichiro Oura <uratec@xxxxxxxxxxxxxxx>
>> >>
>> >> Hi,
>> >>
>> >> This value is node index in "reg.tree".
>> >>
>> >> printf("Splitting Node %d, score %e\n", r->nodeIndex, score);
>> >>
>> >> Index is always positive value.
>> >> I don't know why split is in a loop...
>> >> Could you check the distribution of stream[3]?
>> >>
>> >> Regards,
>> >> Keiichiro Oura
>> >>
>> >>
>> >> 2012/2/23 li jay <lij.acd@xxxxxxxxx>:
>> >> > Thank you for your reply.
>> >> >
>> >> > I've tried HTS2-2, replacing the HTS commands with the ones of
>> >> > HTS-2.2.
>> >> > The
>> >> > result was exactly the same as the one of HTS-2.1.1. The score
>> >> > stayed
>> >> > the
>> >> > same, and the node split endlessly.
>> >> >
>> >> > What do you mean by 'Splitting Node' is negative value? You mean the
>> >> > score?
>> >> >
>> >> > Regards,
>> >> > Jay
>> >> >
>> >> > 2012/2/22 Keiichiro Oura <uratec@xxxxxxxxxxxxxxx>
>> >> >>
>> >> >> Hi,
>> >> >>
>> >> >> Could you try HTS-2.2?
>> >> >> I don't know why 'Splitting Node' is negative value.
>> >> >>
>> >> >> Regards,
>> >> >> Keiichiro Oura
>> >> >>
>> >> >> 2012/2/22 li jay <lij.acd@xxxxxxxxx>:
>> >> >> > Hi,
>> >> >> >
>> >> >> > I've been trying to build a regression tree for speaker
>> >> >> > adaptation. I
>> >> >> > am
>> >> >> > using HTS 2.1.1. I've trained a average voice model from 4000
>> >> >> > sentences
>> >> >> > (about 2.5 hrs) of 20 speakers. It was successful to generate
>> >> >> > voice
>> >> >> > using
>> >> >> > the average voice model. I wanted to apply speaker adaptation on
>> >> >> > this
>> >> >> > average voice model, so I tried to build a regression tree with
>> >> >> > the
>> >> >> > command
>> >> >> > below:
>> >> >> > /usr/local/HTS-2.1.1/bin/HHEd -A -B -C
>> >> >> > /home/jay/TTS/try/AST_female_20_speakers_2/configs/trn.cnf -D -T 1
>> >> >> > -p
>> >> >> > -i
>> >> >> > -H
>> >> >> > /home/ jay /TTS/try/AST_female_20_speakers_2/models/cmp/re_clust
>> >> >> > ered.mmf -M /home/
>> >> >> > jay /TTS/try/AST_female_20_speakers_2/models/cmp/regTrees
>> >> >> > /home/ jay /TTS/try/AST_female_20_speakers_2/edfiles/cmp/reg.hed
>> >> >> > /home/
>> >> >> > jay /TTS/try/AST_female_20_speaker
>> >> >> > s_2/data/lists/full.list
>> >> >> >
>> >> >> > The problem was that splitting of nodes did finish. It seemed to
>> >> >> > be
>> >> >> > in a
>> >> >> > loop, and the score stayed the same. So the HHEd command cannot
>> >> >> > stop. The
>> >> >> > log file shows as below:
>> >> >> >
>> >> >> > HTK Configuration Parameters[10]
>> >> >> > Module/Tool Parameter Value
>> >> >> > # MINDUR 5
>> >> >> > # MAXSTDDEVCOEF 10
>> >> >> > # APPLYDURVARFLOOR TRUE
>> >> >> > # DURVARFLOORPERCENTILE 1.000000
>> >> >> > # SHRINKOCCTHRESH Vector 4 500.0 100.0 100.0
>> >> >> > 100.0
>> >> >> > # VFLOORSCALESTR Vector 4 0.01 0.01 0.01 0.01
>> >> >> > # MINLEAFOCC 0
>> >> >> > # NATURALWRITEORDER TRUE
>> >> >> > # NATURALREADORDER TRUE
>> >> >> > # APPLYVFLOOR TRUE
>> >> >> >
>> >> >> > // construct regression class tree
>> >> >> > RC 32 reg
>> >> >> > Building regression tree with 32 terminals (4 streams)
>> >> >> > Creating regression class tree with ident reg.tree and baseclass
>> >> >> > reg.base
>> >> >> > Splitting Node 1, score 1.000000e+10
>> >> >> > (Stream splitting)
>> >> >> > Splitting Node 3, score 1.000000e+10
>> >> >> > (Stream splitting)
>> >> >> > Splitting Node 5, score 1.000000e+10
>> >> >> > (Stream splitting)
>> >> >> > Splitting Node 7, score 1.000000e+10
>> >> >> > (MSD splitting)
>> >> >> > Splitting Node 6, score 1.000000e+10
>> >> >> > (MSD splitting)
>> >> >> > Splitting Node 10, score 8.998759e+10
>> >> >> > (Stream=3, vSize=1)
>> >> >> > Splitting Node 13, score 2.999760e+10
>> >> >> > (Stream=3, vSize=1)
>> >> >> > Splitting Node 4, score 1.000000e+10
>> >> >> > (MSD splitting)
>> >> >> > Splitting Node 15, score 9.997541e+09
>> >> >> > (Stream=3, vSize=1)
>> >> >> > Splitting Node 19, score 9.997541e+09
>> >> >> > (Stream=3, vSize=1)
>> >> >> > Splitting Node 21, score 9.997541e+09
>> >> >> > (Stream=3, vSize=1)
>> >> >> > ...
>> >> >> > ...
>> >> >> > ...
>> >> >> > Splitting Node -16495, score 9.997541e+09
>> >> >> > (Stream=3, vSize=1)
>> >> >> > Splitting Node -16493, score 9.997541e+09
>> >> >> > (Stream=3, vSize=1)
>> >> >> > Splitting Node -16491, score 9.997541e+09
>> >> >> > (Stream=3, vSize=1)
>> >> >> >
>> >> >> > Could you do me a favor to help the problem? My questions are:
>> >> >> > 1: What could be the reason or problem result in this endless
>> >> >> > splitting
>> >> >> > node
>> >> >> > situation.
>> >> >> > 2:Could it be the problem with the average modeling? Is there any
>> >> >> > option
>> >> >> > to
>> >> >> > enable average modeling? I trained the average model just as
>> >> >> > speaker
>> >> >> > dependent model with the same scripts, except the training data
>> >> >> > from
>> >> >> > different people.
>> >> >> >
>> >> >> > Thank you.
>> >> >> >
>> >> >> > Regards,
>> >> >> > Jay
>> >> >>
>> >> >
>> >>
>> >
>>
>