[hts-users:02200] Re: TRANSP of monophone reestimation

["Heiga ZEN (Byung Ha CHUN)" <heiga.zen@xxxxxxxxxxxxxxxxx>]

Hi,

燕鹏举 wrote (2009/08/31 11:06):

> I'm studying the standard HTS demo process (Training.pl), I found that the
> TRANSP during monophone re-estimation isn't updated appropriately.
> 
> Before the step of $ERST0, the transition matrices contain non-0
> probabilities to current and the immediate next states, say
> 
> <TRANSP> 7
>  0.000000e+00 1.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
> 0.000000e+00 0.000000e+00
>  0.000000e+00 4.952075e-01 5.047925e-01 0.000000e+00 0.000000e+00
> 0.000000e+00 0.000000e+00
>  0.000000e+00 0.000000e+00 7.473042e-01 2.526958e-01 0.000000e+00
> 0.000000e+00 0.000000e+00
>  0.000000e+00 0.000000e+00 0.000000e+00 7.416168e-01 2.583832e-01
> 0.000000e+00 0.000000e+00
>  0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 9.256996e-01
> 7.430040e-02 0.000000e+00
>  0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
> 5.919777e-01 4.080223e-01
>  0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
> 0.000000e+00 0.000000e+00
> 
> But after $ERST0 (HERest on monophones), the transition probability to the
> current state is 0, say
> 
> <TRANSP> 7
>  0.000000e+00 1.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
> 0.000000e+00 0.000000e+00
>  0.000000e+00 0.000000e+00 1.000000e+00 0.000000e+00 0.000000e+00
> 0.000000e+00 0.000000e+00
>  0.000000e+00 0.000000e+00 0.000000e+00 1.000000e+00 0.000000e+00
> 0.000000e+00 0.000000e+00
>  0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 1.000000e+00
> 0.000000e+00 0.000000e+00
>  0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
> 1.000000e+00 0.000000e+00
>  0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
> 0.000000e+00 1.000000e+00
>  0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
> 0.000000e+00 0.000000e+00
> 
> You can check the file monophone.mmf.embedded.gz in your own cmp folder.
> 
> Can anybody give any hint? Thanks.

because it's an HSMM rather than HMM.  Self-state transition
probabilities of HSMMs are always 0.

HERest supports both HMM & HSMM training.  However, HInit & HRest
don't (only HMM).  When HERest loads both state-output distribution
mmf and state-duration distribution mmf, HERest automatically converts
HMM into HSMM.  Therefore, until the first HERest, state-output
distribution mmf is HMM.  Once you update state-output &
state-duration distribution mmfs, they become HSMM.

Regards,

Heiga ZEN (Byung Ha CHUN)

-- 
Heiga ZEN (Byung Ha CHUN)
Speech Technology Group
Cambridge Research Lab
Toshiba Research Europe
phone: +44 1223 436975

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