John
Guest
|
 Posted:
Thu Dec 01, 2005 12:51 am Post subject:
too many combinations: Transition probability etc. |
|
|
Hi
I am trying to do some statistics, but I don't know how to solve the problem
I am working on.
I have N speech segments and I perform a 10th order LPC-analysis of each
segment and get a 10-dimensional LPC-vector A(j)=[a1(j),a2(j),....a10(j)]
for j=1 to N.
I then convert all A(j) to B(j)=[c1(j),c2(j),......,c10(j)] where the
coefficients of B(j) are the LSF-coefficients corresponding to the
LPC-vector A(j).
I want to figure out what:
- the probability of B(j) given B(j-1) is ? (transition probability)
- the probability of B(j) ?
How do I do that?
My thoughts:
The first step would be to define a discrete space S of outcomes for B(j),
but the number of possible outcomes is very large. The coefficients of B(j)
each
have a dynamic range from 0 to pi. If I use a discrete range from
0,0.01,0.02,..........,3.14 that is 315 possible outcomes for any
coefficient in B(j). Since B(j) is a 10-dimensional
vector I have 315^10 possible outcomes in the space S. That number is way
too big to do any realistic computation in matlab...... |
|
Peter K.
Guest
|
| Posted:
Thu Dec 01, 2005 1:17 am Post subject:
Re: too many combinations: Transition probability etc. |
|
|
John wrote:
| Quote: | I am trying to do some statistics, but I don't know how to solve the problem
I am working on.
I have N speech segments and I perform a 10th order LPC-analysis of each
segment and get a 10-dimensional LPC-vector A(j)=[a1(j),a2(j),....a10(j)]
for j=1 to N.
I then convert all A(j) to B(j)=[c1(j),c2(j),......,c10(j)] where the
coefficients of B(j) are the LSF-coefficients corresponding to the
LPC-vector A(j).
I want to figure out what:
- the probability of B(j) given B(j-1) is ? (transition probability)
- the probability of B(j) ?
How do I do that?
|
1. Calculate Pr[ B(j) | B(j-1) ].
2. Calculate Pr[ B(j) ] = sum{k = 0 to N-1} Pr[ B(j) | B(k) ]
| Quote: | My thoughts:
The first step would be to define a discrete space S of outcomes for B(j),
but the number of possible outcomes is very large. The coefficients of B(j)
each
have a dynamic range from 0 to pi. If I use a discrete range from
0,0.01,0.02,..........,3.14 that is 315 possible outcomes for any
coefficient in B(j). Since B(j) is a 10-dimensional
vector I have 315^10 possible outcomes in the space S. That number is way
too big to do any realistic computation in matlab......
|
Don't quantize nearly so finely and use vector quantization rather than
quantizing the individual elements.
Ciao,
Peter K. |
|
FAQ
Memberlist
Register
Profile
Log in to check your private messages
Log in