*Subject*: [hts-users:03184] Re: Problem of building regression tree (average voice model)*From*: "Heiga ZEN (Byung Ha CHUN)" <heigazen@xxxxxxxxxx>*Date*: Fri, 24 Feb 2012 09:30:43 +0000*Authentication-results*: mr.google.com; spf=pass (google.com: domain of heigazen@xxxxxxxxxx designates 10.152.109.99 as permitted sender) smtp.mail=heigazen@xxxxxxxxxx; dkim=pass header.i=heigazen@xxxxxxxxxx*Delivered-to*: hts-users@xxxxxxxxxxxxxxx*Dkim-signature*: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=gamma; h=mime-version:in-reply-to:references:date:message-id:subject:from:to :content-type:x-system-of-record; bh=bHIIOvx5eG+xjBW0RGRsZmVxZ8Zprw0fpZN1zAY7I8M=; b=ialjgZEjSN7XioFyj7xXsJDjZG+AcCx6JoquPqxQEeNB9AACXw2m1IQB7Dt2frC+De zi7ZyzpUnXxLbqxdRRFn2VEQmyWbuhZXU5RYYG2DwKTSBKVgdLmDEYSwS1hus+CHpKeK albJW057uVS/UJqFWXa/Hk+M9CH6Wy7f0p0BE=

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

2012/02/24 9:23 "li jay" <lij.acd@xxxxxxxxx>:

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

>> >> >>

>> >> >

>> >>

>> >

>>

>

**Follow-Ups****[hts-users:03186] Re: Problem of building regression tree (average voice model)**,*li jay*

**References****[hts-users:03173] Problem of building regression tree (average voice model)**,*li jay***[hts-users:03174] Re: Problem of building regression tree (average voice model)**,*Keiichiro Oura***[hts-users:03176] Re: Problem of building regression tree (average voice model)**,*li jay***[hts-users:03177] Re: Problem of building regression tree (average voice model)**,*Keiichiro Oura***[hts-users:03179] Re: Problem of building regression tree (average voice model)**,*li jay***[hts-users:03180] Re: Problem of building regression tree (average voice model)**,*Keiichiro Oura***[hts-users:03181] Re: Problem of building regression tree (average voice model)**,*li jay***[hts-users:03182] Re: Problem of building regression tree (average voice model)**,*Keiichiro Oura***[hts-users:03183] Re: Problem of building regression tree (average voice model)**,*li jay*

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