Subject : Signal bias removal

Why ?

An acoustical mismatch between the training and the testing conditions of hidden Markov model (HMM)-based speech recognition systems .

Mismatch 如何造成的呢 ??

S (t)O S’(t)H(t)

*bias 的影嚮

mean shift

variance 變大

How ?

The bias removal method based on ML

先考慮不知道 bias 這個參數的 likehood

P(X|Λ) =Пmax P(x |ג ) t i t i

x t

X1-u=b1

X2-u=b2

.

.

b=1/NΣ(xi-u)

考慮有常數 b

y = x + b

p(Y|b)=p(Y-b|)

p(Y|b,Λ)=Пmaxp(y-b|ג)

b=1/NΣ(yi-u) bias

X1=y1-b1

Y2=x1=y1-b1

X2=y2-b2

Y3=x2=y2-b2

X3=y3-b3

Iteration 2

Iteration 3

新 feature

新 feature

X3 + HMM Compact model

begin

it

01 It > 4

Sequential VQ• generate 32 codewords of MAT-database

Write codewords to codebook

For all spks

Open files• len, fa ,tab ,bias

For all goodutterances

• read Nframe• read tab

For all frames• Read features

Bias• compute bias for each utterance and iteration 20 times

Write outbias

end

sbr_train.c