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  BGIÁO DC VÀ ĐÀO TO Trường Đại hc Yersin Đà Lt  Khoa Công NghThông Tin -------  ------- XLÝ VÀ NHN DNG TING NÓI LU  ẬN VĂN CỬ   NHÂN TIN HC GIÁO VIÊN HƯỚ NG DN: TS Nguyn Đứ c Minh Niên khóa 2010 - 2014

Bao Cao Khoa Luan

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bao cao khoa luan

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  • B GIO DC V O TO Trng i hc Yersin Lt

    Khoa Cng Ngh Thng Tin ------- -------

    X L V NHN DNG

    TING NI

    LUN VN C NHN TIN HC

    GIO VIN HNG DN:

    TS Nguyn c Minh

    Nin kha 2010 - 2014

  • 1

    NHN XT CA GIO VIN HNG DN

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    Lt, ngythng.nm 2014

    GIO VIN HNG DN

  • 2

    NHN XT CA GIO VIN PHN BIN

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  • 3

    LI CM N

    Xin chn thnh cm n thy Nguyn c Minh tn tnh

    hng dn em em c th hon thnh lun vn ny. Cc bui hc

    cng thy trn khoa cng nhng ti liu m thy cung cp cho

    em tht l qu gi, khng nhng thy dy kin thc chuyn

    ngnh m cn truyn t nhng k nng v phng php hc ting

    anh gip em ci thin hn vn ting anh hin c.

    Em xin gi li cm n n cc thy c trong trng, c bit

    l cc thy c trong khoa Cng Ngh Thng Tin to iu kin tt

    nht em c th hc tp v nghin cu.

    Em cng khng th khng nhc n s ng vin chm sc

    ca gia nh, s cng tc gip v ng h tinh thn ca bn b.

    Em xin c tri n tt c.

    lt, thng 06 nm 2014

    Trn Mnh Hi

  • 4

    MC LC

    NHN XT CA GIO VIN HNG DN .............................................................. 1

    NHN XT CA GIO VIN PHN BIN ................................................................ 2

    LI CM N ............................................................................................................... 3

    LI NI U .............................................................................................................. 5

    DANH SCH HNH V ............................................................................................... 6

    Chng I TNG QUAN V NHN DNG GING NI ........................................... 7

    I. Nhn dng .................................................................................................................. 7

    II. Cc tnh cht c trng ca nhn dng ting ni ...................................................... 11 1. Ting ni con ngi ...................................................................................................................... 11 2. Phn loi nhn dng ting ni ....................................................................................................... 11 3. Nhng kh khn ............................................................................................................................ 12

    III. ng dng .................................................................................................................. 12

    Chng II X L V RT TRCH C TRNG TING NI ............................... 13

    I. Qu trnh x l v ly mu ....................................................................................... 13 1. M hnh tng quan ........................................................................................................................ 13

    II. Rt trch c trng ................................................................................................... 14 1. Phn khung tn hiu....................................................................................................................... 15 2. Ly ca s ..................................................................................................................................... 16 3. Bin i tn hiu sang min tn s (Bin i Fourier ri rc - DFT) ............................................ 20 4. c trng MFCC (Mel Frenquency Cepstral Coefficients) .......................................................... 21 5. c trng M ha d on tuyn tnh (LPC)................................................................................ 25

    III. Nhn xt ................................................................................................................... 30

    Chng III NHN DNG BNG M HNH MNG NEURAL ............................... 31

    I. Tng quan ................................................................................................................ 31

    II. Qu trnh hot ng ................................................................................................. 32 1) T bo ca mng ........................................................................................................................... 32 2) Mng Neural truyn thng nhiu lp ............................................................................................ 34

    a) M hnh c bn: ...................................................................................................................... 34 b) Lut hc ca mng: ................................................................................................................ 34

    III. Qu trnh hun luyn ................................................................................................ 36 1) Thut ton lan truyn ngc ..................................................................................................... 36

    a) Khi nim v tng ............................................................................................................. 36 b) M hnh minh ha ................................................................................................................... 36 c) Tnh ton cc gi tr v tham s ............................................................................................ 38 d) Cc bc xy dng thut ton ............................................................................................... 42

    2) M phng trn Matlab v ng dng vo nhn dng ting ni ................................................ 44

    IV. Kt lun .................................................................................................................... 50

    KT LUN ................................................................................................................. 51

    TI LIU THAM KHO: .......................................................................................... 53

  • 5

    LI NI U Ngy nay vi s pht trin mnh m ca cng ngh, con ngi t ng ha

    kh nhiu cng vic m ngy trc phi tn sc ngi l chnh. Cc h thng

    thng minh ra i nng cao nng sut cng nh cht lng ca cng vic. Tuy

    nhin iu khin my mc, con ngi phi lm kh nhiu thao tc tn nhiu

    thi gian v cn phi c o to. iu ny gy tr ngi khng t i vi vic s

    dng cc my mc, thnh tu khoa hc k thut. Trong khi , nu iu khin my

    mc thit b bng ting ni s d dng hn. Nhu cu iu khin my mc thit b

    bng ting ni cng bc thit hn i vi cc thit b cm tay, nh: in thoi di

    ng, my Palm/Pocket PC,

    Con ngi d dng hiu nhau nh ngn ng, nhng iu l kh khn

    i vi my mc. Nhng khng phi l khng lm c, trn th gii hnh

    thnh cc h thng nhn dng ting ni t n gin ti cc h thng cc k phc

    tp, chng t rng my mc sau qu trnh hun luyn ca con ngi th chng cng

    c kh nng hiu chng ta qua ting ni.

    Lun vn ny em tp trung vo nghin cu hai phn ln trong nhn dng ting

    ni l rt trch c trng v phng php Neural cho nhn dng v hun luyn.

    Lun vn gm cc phn chnh nh sau:

    CHNG I: Cung cp ci nhn tng quan v tn hiu ting ni v nhn

    dng ting ni.

    CHNG II: X l v rt trch c trng. Gii thiu cc b lc c bn

    cho x l tn hiu, m hnh v cc phng php rt trch c trng

    CHNG III: Phng php nhn dng Mng Neural. Gii thiu v

    mng Neural, phng php hun luyn trn mng.

  • 6

    DANH SCH HNH V

    Hnh 1. 1 Cu trc ca tai ngi _________________________________________________ 7 Hnh 1. 2 M hnh nhn dng ting ni ____________________________________________ 8 Hnh 1. 3 M hnh m phng phng php HMM ___________________________________ 10

    Hnh 2. 1 S cc khi ca m hnh ly mu _____________________________________ 13 Hnh 2. 2 Trnh t rt trch c trng ____________________________________________ 14 Hnh 2. 3 Khung tn hiu vi N = 256 ____________________________________________ 15 Hnh 2. 4 Phn on ting ni thnh cc khung chng lp ____________________________ 16 Hnh 2. 5 Ca s Hamming theo min thi gian v tn s _____________________________ 17 Hnh 2. 6 Ca s Hann theo min thi gian v tn s. _______________________________ 18 Hnh 2. 7 Ca s Tam gic theo min thi gian v tn s _____________________________ 19 Hnh 2. 8 Minh ha ca s hnh ch nht _________________________________________ 19 Hnh 2. 9 m a theo ca s Hann _____________________________________________ 20 Hnh 2. 10 m a vi ca s Hamming _________________________________________ 20 Hnh 2. 11 Minh ha bin i Fourier ____________________________________________ 21 Hnh 2. 12 a) Mel v tn s_____________________________________________________ 22 Hnh 2. 13 Minh ha b lc tam gic _____________________________________________ 24 Hnh 2. 14 B lc tam gic thc t trn min tn s _________________________________ 25 Hnh 2. 15 S x l LPC dng cho trch c trng ting ni ________________________ 27

    Hnh 3. 1 M hnh chi tit 1 t bo neural _________________________________________ 32 Hnh 3. 2 M hnh mng nhiu lp _______________________________________________ 34 Hnh 3. 3 M hnh tng qut 3 lp _______________________________________________ 37 Hnh 3. 4 M hnh chi tit c bn _______________________________________________ 37 Hnh 3. 5 Hnh minh ha th _________________________________________________ 44 Hnh 3. 6 Hnh minh ha qu trnh hun luyn _____________________________________ 46 Hnh 3. 7 th dng tam gic (xi) ______________________________________________ 46 Hnh 3. 8 Mng Neural s dng _________________________________________________ 47

  • 7

    Chng I TNG QUAN V NHN DNG GING NI

    I. Nhn dng

    Nh chng ta bit nhn bit c ting ni l mt kh nng tuyt vi m

    to ha ban cho chng ta, nh i mt gip con ngi nhn thy c s chuyn

    ng bin i ca th gii th i tai gip con ngi nghe c nhng m thanh

    m mi trng xung quanh mun truyn t ti chng ta. Qu trnh nhn thc

    c mt m than h, ting ni trong c th chng ta l mt qu trinh v cng

    phc tp v tinh vi.

    Sng m thanh c truyn vo trong tai ngi v to nn cc rung ng c

    hc trn cc b phn trong tai. Trong cng ca tai l c tai, y l ni tn hiu

    c phn tch thnh nhng khung tn s nht nh.

    Hnh 1. 1 Cu trc ca tai ngi

  • 8

    Qu trnh x l v nhn dng trong b no con ngi l mt qu trnh

    rt phc tp v chnh xc v cng cao. Cc m hnh nhn dng ting ni

    v mt l thuyt u da trn s m phng ging nh tai ngi, v cu trc

    ln hot cch thc hot ng.

    Di y l m hnh nhn dng ting ni tng qut:

    Xy dng c s d liu ting

    ni

    X l v rt trch c trng

    Nhn dng so khp mu

    Kt qu

    Tn hiu hc Tn hiu cn nhn dng

    Hun luyn

    Tn hiu ting ni

    Hnh 1. 2 M hnh nhn dng ting ni

  • 9

    Tn hiu ting ni c thu li thng qua cc thit b ghi m nh:

    microphone v n c chuyn sang tn hiu in.

    X l v rt trch c trng: l qu trnh tinh chnh tn hiu u vo, to

    ra tn hiu mu tt nht. Sau s dng cc phng php rt trch

    cc c trng c bn ca tn hiu .

    Xy dng c s d liu ting ni: Tn hiu ting ni sau khi c x l

    v rt trch c trng c lu li thng qua qu trnh hun luyn hay

    hc bng cc m hnh nhn dng.

    Nhn dng so snh khp mu: Tn hiu ting ni sau khi c x l v

    rt trch c trng c th l tn hiu cn nhn dng. N c em so

    snh vi mu bng cc phng php nhn dng ting ni. Nu nh tn

    hiu so khp nht ng vi mt lp tn hiu no th h thng nhn

    dng xc nh tn hiu thuc vo nhm tn hiu no vi mt t l

    nht nh.

    Kt qu: tn hiu u ra s phc v cho cc ng dng, ty ng dng m

    kt qu u ra s khc nhau.

    Cc m hnh nhn dng ting ni ph bin:

    M hnh Markov - n (Hidden Markov Model HMM)

    M hnh Markov n (Hidden Markov Model - HMM) l m hnh

    thng k trong h thng c m hnh ha c cho l mt qu trnh Markov

    vi cc tham s khng bit trc v nhim v l xc nh cc tham s n t cc

    tham s quan st c, da trn s tha nhn ny. Cc tham s ca m hnh

    c rt ra sau c th s dng thc hin cc phn tch k tip.

  • 10

    Trong mt m hnh Markov in hnh, trng thi c quan st trc

    tip bi ngi quan st, v v vy cc xc sut chuyn tip trng thi l cc

    tham s duy nht. M hnh Markov n thm vo cc u ra: mi trng thi c

    xc sut phn b trn cc biu hin u ra c th. V vy, nhn vo dy ca cc

    biu hin c sinh ra bi HMM khng trc tip ch ra dy cc trng thi.

    M hnh mng Neural

    (s c trnh by k chng III)

    Hnh 1. 3 M hnh m phng phng php HMM

  • 11

    II. Cc tnh cht c trng ca nhn dng ting ni

    1. Ting ni con ngi

    Ting ni con ngi s dng hng ngy mang bn cht ca sng m

    thanh, n lan truyn trong khng kh nh s gin n ca khng kh. Tn hiu

    m thanh ting ni l tn hiu bin thin lin tc v mt thi gian. Di tn m

    tai ngi c th nghe c l 20Hz n 20kHz.

    Ting ni c to thnh t cc chui m v lin tip, s sp xp

    nhng m v ny c chi phi bi cc quy lut ngn ng cho nn cc m

    hnh ton hc khi c p dng th phi gn b mt thit vi cc quy lut

    ngn ng.

    Ba c trng:

    m vc hay cao (Pitch) l cm nhn s rung ng ca

    tn s ca m thanh trong mt khong thi gian. m no cng c mt cao

    nht nh, trm bng ph thuc vo tn s giao ng v i vi ting ni

    th tn s dao ng ca dy thanh quy nh quyt nh cao ca ging ni

    con ngi. V mi ngi c mt cao ging ni khc nhau.

    m nhn l cm nhn cng rung ng ca m thanh qua

    mt khong thi gian v cao . Cng chnh l to nh ca m thanh,

    cng cng ln th m cng truyn c xa hn, nu xt v mt sng m

    th cng chnh l bin giao ng, n quyt nh nng lng ca sng

    m.

    m sc l mt thut ng trong m nhc, n th hin s hi ha

    cc c tnh ng ca m thanh nh l iu bin, tng ln hay rt xung ca

    tn hiu. Cng mt cao nhng mi ngi li c mt m sc khc nhau

    2. Phn loi nhn dng ting ni

    Nhn dng theo cc t hay cc m ri rc.

    Nhn dng ting ni c lp hay ph thuc vo ngi ni.

    Nhn dng vi t in c va, nh hay c ln.

    Nhn dng vi mi trng nhiu cao hay thp.

  • 12

    3. Nhng kh khn

    Tc ni ca ngi khc nhau, c ngi ni nhanh c ngi ni chm.

    di ngn ca m khc nhau.

    Kt qu phn tch hai ln i vi mt ngi ni khc nhau.

    Cht ging theo vng min th cht ging khc nhau hoc l ging nam hay

    ging n.

    Cc yu t ca mi trng lm nhiu tn hiu, i khi b nhiu t chnh thit

    b thu.

    III. ng dng

    iu khin giao tip khng dy: chng hn h thng my tnh nhn lnh iu

    khin bng ting ni ca con ngi nh: chy chng trnh, tt my. Cc

    h thng thng minh nhn lnh trc tip ca con ngi thng qua ting ni.

    c chnh t: c s dng nhiu nht trong cc h nhn dng. Nhp liu

    bng ting ni thay v bng cch th cng l ngi nh my.

    in thoi lin lc: mt s h thng cho php ngi s dng c tn ngi

    trong danh b thay v bm s. Truy cp cc ng dng, vit tin nhn bng ting

    ni

  • 13

    Chng II X L V RT TRCH C TRNG TING NI

    I. Qu trnh x l v ly mu

    1. M hnh tng quan

    Trong x l tn hiu, ly mu l chuyn i mt tn hiu lin tc thnh mt

    tn hiu ri rc. Mc d c s t do trong vic la chn th t cc mu tnh hiu

    c to ra t nhng tn hiu tng t. Nhng y ti xin a ra m hnh x l

    v ly mu ti u nht, cc khi trong m hnh c th thay i v tr cho nhau, ty

    vo tng trng hp.

    Khi lc thp v chng bit danh: theo nh l ly mu Nyquist-

    Shannon th tn s ly mu (fc) s l cao gp i rng ca di tn, hay tn s

    ln nht. V vy, ta chn tn s ly mu s l 40 44kHz (gp i tn s nghe

    ca tai ngi 20kHz). Nh vy c th chng Bit danh. Khi lc thp s lc

    cc tn hiu c tn s cao to mn cho tn hiu u ra.

    Khi lc cao: khi ny ct b cc tn hiu c tn s thp, to bin

    thin nh nht.

    Tin nhn: Tng cng tn hiu, lm r cc c trng ca tn hiu.

    Lng t ha: vic biu din s tn hiu i hi lng t ha mi mu tn hiu

    vi mt gi tr ri rc hu hn. Mi mu tn hiu c lng t ha, m ha ri

    truyn i. Bn thu nhn tn hiu s gii m v thu c tn hiu tng t.

    Hnh 2. 1 S cc khi ca m hnh ly mu

  • 14

    II. Rt trch c trng

    cho vic nhn dng ting ni d dng hn v gim chi ph th vic rt

    trch c trng tn hiu l mt phn v cng quan trng. Tn hiu th ban u c

    dung lng rt ln, v phc tp cao. Vic rt trch cc c trng t tn hiu

    s gip cho khu so snh khp mu d dng hn, v to ra chnh xc cao

    hn.

    Cc bc rt trch c trng:

    X l v lm r tn hiu

    Phn khung tn hiu

    Ly ca s

    Phn tch c trng

    Tn

    hiu

    Hnh 2. 2 Trnh t rt trch c trng

  • 15

    1. Phn khung tn hiu

    Tn hiu sau qu trnh ly mu c phn khung, chng hn mt lung

    ca tn hiu m thanh c chuyn thnh tp cc khung tn hiu. Trong bc

    ny tn hiu c chia thnh cc khung mi khung ng vi N mu, khong

    cch gia cc khung l M mu.. di thi gian cho mi khung khong

    20~30ms. Nu thi gian khung qu ln, chng ta khng th nm bt cc c

    im khc nhau theo thi gian ca tn hiu. Ngc li, nu thi gian khung qu

    nh, th chng ta khng th rt trch cc c trng hp l hoc c gi tr. Ni

    chung, mt khung tn hiu cn cha vi chu k c bn ca tn hiu m thanh

    nht nh, thng kch thc ca khung bng vi m c s 2 (chng hn 256,

    512, 1024..) nh vy c kh nng bin i Fourier nhanh.

    Nu chng ta mun gim bt s khc bit gia cc khung ln cn, chng

    ta c th s dng cc khung chng lp nhau, thng thc hin chng lp 1/3

    Hnh 2. 3 Khung tn hiu vi N = 256

  • 16

    hoc 2/3 ca khung tn hiu gc. Khung chng lp nhiu, yu cu tnh ton cng

    nhiu hn. Nh hnh 1.2 minh ha chng lp 1/3. Khung th nht c N mu,

    khung th hai bt u t mu th M v kt thc v tr M+N. Khi M N th s

    khng c s chng lp gia cc khung k nhau, dn n mt s mu ting ni b

    mt (tc l khng xut hin trong bt k khung no).

    Hnh 2. 4 Phn on ting ni thnh cc khung chng lp

    Gi s cc tn hiu m thanh trong mt khung l khng thay i, chng ta

    c th trch cc c trng chng hn nh t l im qua zero, m lng, cao ,

    MFCC, LPC,

    Chng ta c th thc hin pht hin im u v cui ca tn hiu da t

    l im qua zero v m lng, v gi li cc khung tn hiu c ting ni phn

    tch v sau.

    2. Ly ca s

    Bc tip theo trong x l l ly ca s tn hiu ng vi mi khung gim

    thiu s gin on tn hiu u v cui mi khung. Gi mu th n ca khung

    th l l lhn , w(n) l hm ca s:

    ln = lhn . w(n) n {0,1,, N-1}

    Cc dng ca s tn hiu:

  • 17

    Trong x l tn hiu s, cc ca s thng dng c biu din thng qua

    ca s Hamming:

    = 0.54 0.46 cos 2

    1

    Hnh 2. 5 Ca s Hamming theo min thi gian v tn s

    Vi ca s Hamming ph tn s ri xung mt cch nhanh chng, v th n

    cho php c lp tn hiu tt nht. Tuy nhin, cc sng m c cao ln b gi li

    hon ton mt cch bng phng v n che ph phn ln ph tn s. Mc d vy,

    n vn ph bin nht nh vo tnh k tha.

    Ca s Hann (Hanning): y l mt loi khc ca ca s Hamming. S khc

    bit gia chng l ca s Hann t 0 cho n=0 v n= N-1. Gi tr Zero khc

    ui c th c hoc khng mong mun ph thuc vo trng hp chng ta x l

    tn hiu v gii thch cho iu ny l khi dn tin v Zero, mt d liu khng

    c s dng. Tuy nhin trong nhn dng ging ni, n khng c vn g ht

    bi v chng thng c va khung chng ln nhau trong vic tnh ton c

    trng .

  • 18

    = 0.5 1 cos 2

    1

    Vi ca s Hamming th cc tn s thp ri xung mt cch nhanh chng v

    sau gn nh tr thnh phng vi cc tn s cao. Mt khc, ca s Hann ri

    chm hn mt cht vi tn s cao nhng nhanh chng vi tn s thp. V vy,

    vi mi loi u c u im hoc hn ch ring ca chng.

    Ca s Tam gic: nh tn gi th n ch l mt tam gic vi nh nm

    trung tm ca ca s (n =

    2). Ca s ny quan trng v thng c s dng

    trong phng php MFCC. Biu thc ca ca s tam gic:

    = 1 2 + 1

    1

    Hnh 2. 6 Ca s Hann theo min thi gian v tn s.

  • 19

    Nh ph tn s hnh 1.5 th n ri xung kh t ngt. Cc sng c tn s

    cao c rng nhiu hn so vi hai ca s trn.

    Ca s hnh ch nht:

    = 1, 0 0,

    Hnh 2. 7 Ca s Tam gic theo min thi gian v tn s

    Hnh 2. 8 Minh ha ca s hnh ch nht

  • 20

    Mt s v d minh ha:

    3. Bin i tn hiu sang min tn s (Bin i Fourier ri rc - DFT)

    Bc tip theo trong vic x l tn hiu ting ni c th tnh ton c

    cc c trng quang ph l bin i Fourier ri rc trn cc ca s tn hiu.

    =

    2

    1

    =0

    = ()

    2

    1

    =0

    Hnh 2. 9 m a theo ca s Hann

    Hnh 2. 10 m a vi ca s Hamming

  • 21

    Khi k = {0,1,,N-1} l ch s ca min tn s vi k = 0 tng ng vi thnh phn DC v k = N/2 ng vi tn s gp.

    Php bin i nhanh fourier ri rc (FFT)

    Php bin i nhanh ny u da trn k thut phn chia theo c s 2,

    ngha l thay v bin i trn ton b tn hiu th php bin i ny s phn chia

    chui tn hiu thnh 2 chui tn hiu con, v li p dng php bin i ln na

    cho 2 phn ny mt cch quy. Do php chia cho 2, nn chui tn hiu i hi

    phi c chiu di l ly tha ca 2 (iu ny c th d dng gii quyt c

    bng cch tng kch thc chui tn hiu ln v in 0 vo).

    4. c trng MFCC (Mel Frenquency Cepstral Coefficients)

    nh ngha Mel (Melody): Mel l t vit tt ca m iu (melody), n l

    mt n v ca m vc.N c xc nh l bng vi 1000 Pitch trong mt tn

    s m vc 1000 Hz vi bin l 40dB nm trn ngng nghe.

    Hnh 2. 11 Minh ha bin i Fourier

  • 22

    c trng trch ra nh da trn kh nng cm nhn m ca thnh gic con

    ngi, v thang o trong h thng nhn dng ca con ngi khng phi l thang

    tuyn tnh. ng vi MFCC th ta dng thang Mel.

    Qu trnh trch c trng bng MFCC:

    a)

    b)

    DFT

    Lc vi thang Mel v Log()

    Bin i Cosin

    Tn

    hiu

    Ma trn tn hiu

    Hnh 2. 12 a) Mel v tn s

    b) Mel v tn s c chia trn thang Log

  • 23

    Ta c cng thc nh ngha cho MFCC:

    = 2 1

    2

    1

    =0

    Trong lCm l bin i cosin ri rc (DCT) :

    = 2

    Thang Mel: =

    = {0,1, , 1

    Ma trn l ma trn th (m,k) ca ma trn , {: }

    H s am:

    = 1

    , = 0

    2

    , > 0

  • 24

    Lc tn hiu theo thang Mel

    Hnh 2. 13 Minh ha b lc tam gic

    Dy b lc Mel-scale bao gm mt dy cc b lc tam gic chng ln

    nhau vi tn s v rng dy tnh theo t l tn s Mel. T l tn s Mel, ging

    nh t l Bark s dng cho phng php PLP, c da trn nhng kt qu nghin

    cu tm l t con ngi. Mi khong ngh trong t l Mel ng vi mt cao

    tng i ca mt tone m con ngi cm nhn.

  • 25

    Hnh 2. 14 B lc tam gic thc t trn min tn s

    Sau chng ta ly Logaric v bin i Cosin (DCT) chng ta s c c

    cc ma trn c trng.

    5. c trng M ha d on tuyn tnh (LPC)

    LPC l mt trong nhng phng php c s dng nhiu nht trong lnh vc

    x l ting ni. Bi l n cung cp cng c d tm mt cch ng n v tc

    tnh ton nhanh. Ngun gc c bn ca phng php ny l cc mu tn hiu ting

    ni c xp x ha nh l t hp tuyn tnh ca mt s mu trong qu kh.

    Nguyn l c bn ca LPC lin h mt thit vi m hnh tng hp ting ni, trong

    ch ra rng tn hiu ting ni c th c coi nh l kt qu u ra ca h tuyn

  • 26

    tnh bin i theo thi gian v c kch thch bi cc xung tun hon hay l cc

    nhiu ngu nhin.

    tng c bn ca phng php LPC l ti thi im n, mu ting ni s(n)

    c th c xp x bi mt t hp tuyn tnh ca p mu trc .

    = (1)

    =1

    V sai s d on l :

    = = + (2

    =1

    )

    Bi ton c bn ca phn tch tin on tuyn tnh l xc nh tp hp cc

    h s tin on ai trc tip t tin hiu ting ni. Bi v bn cht thay i theo thi

    gian ca tn hiu ting ni nn cc h s tin on phi c tnh trong cc on

    ngn tn hin. Cch tip cn c bn l tm mt tp cc h s tin on m sai s

    tin on l nh nht i vi mt on ngn tn hiu.

    Vi cch tip cn trn s hng n mt vi kt qu hu ch m c th khng

    c quan st thy ngay lp tc, nhng c th iu chnh bng nhiu cch. i vi

    xung tun hon, n c ngha rng e(n) s bao gm mt chui cc xung ; V d, e(n)

    s tr nn nh trong phn ln thi gian. Do , vic tm cc m ti thiu ho sai

    s tin on ph hp vi nhn xt ny. Th hai, da vo thc t l nu tn hiu

    c sinh ra bi cng thc (l) vi khng c s bin i v thi gian ca cc h s

    v c kch thch bng cch mt xung n l hay mt chui nhiu trng khng

    thay i, th n c th thy rng cc h s d on c kt qu t vic ti thiu ho

    bnh phng sai s tin on ging vi h s ca cng thc (l). Cui cng, s iu

    chnh hp l cho vic ti thiu ho sai s hnh phng trung hnh, sai s tin on

    nh l c s cho vic xc nh cc tham s ca m hnh l cch tip cn hng n

    tp ca cc cng thc tuyn tnh.

  • 27

    Da vo phng php d on tuyn tnh ngi ta p dng n vi nhiu

    phng thc khc nhau ty vo m hnh sng tn hiu ting ni. Mt s phng

    php :

    Phng php hip phng sai

    Phng php t tng quan

    Phng php ro

    Phng php b lc o

    Phng php d ph

    Phng php kh nng cc i

    Phng php dn xut ni b

    Trong thc t th phng php t tng quan l thng c s dng nht.

    Hnh xx trnh by qu trnh x l LPC rt trch c trng ting ni. Cc

    bc tin hnh c bn sau:

    Phn tch tng quan: Mi khung sau khi c ly ca s s c a qua

    bc phn tch t tng quan v cho ra (p + 1) h s t tng quan

    Ma trn vector c trng

    Phn tch tng quan

    Phn tch LPC

    Phn tch Cepstral

    Tn

    hiu

    p

    Hnh 2. 15 S x l LPC dng cho trch c trng ting ni

  • 28

    =

    1

    =0

    + 1

    0

    Phn tch LPC: Bc ny, ta s chuyn mi khung gm (p + 1) h s t tng

    quan thnh p h s LPC bng cch dng thut ton Levinson Durbin.

    nh ngha E:

    (0) = (0)

    for (q = 1 to Q),

    1.

    =

    1( )

    1=1

    (1)

    2.

    ()

    =

    3. for (j = 1 to Q)

    ()

    = (1)

    (1)

    endfor

    () = 1 2

    (1)

    endfor

    Lc ny, ta c th dng cc h s LPC lm vector c trng cho tng

    khung. Tuy nhin, c mt php bin i to ra dng h s khc c tp trung cao

    hn t cc h s LPC, l php phn tch Cepstral.

  • 29

    Phn tch Cepstral: T p h s LPC mi khung, ta dn xut ra q h s

    cepstral c(m) theo cng thc quy sau:

    0 = 2

    = +

    1

    =1

    1

    =

    1

    =1

    Trong 2 c gi l li ca m hnh, ta thng chn

    3

    2

    t trng s cho cc h s Cepstral: Do nhy ca cc h s cepstral

    cp thp lm cho ph b dc v do nhy ca cc h s cepstral cp cao gy ra

    nhiu nn ta thng s dng k thut t trng s lm gim thiu cc nhy

    ny:

    i(m) = c(m). w(m)

    Trng s w(m):

    = 1 +

    2sin

    1

    Nhn xt

    M hnh LPC l m hnh c bit thch hp cho tn hiu ting ni. Vi min

    ting ni hu thanh c trng thi gn n nh, m hnh tt c cc im cc i ca

    LPC cho ta mt xp x tt i vi ng bao ph m, vi ting ni v thanh, m

    hnh LPC t ra t hu hiu hn so vi hu thanh, nhng n vn l m hnh hu ch

  • 30

    cho cc mc ch nhn dng ting ni. M hnh LPC n gin v d ci t trn

    phn cng ln phn mm.

    III. Nhn xt Rt trch c trng mt gia on quan trng, vi cc c trng thu c

    sau qu trnh x l th s c dng vo qu trnh hc hay nhn dng sau ny. V

    vy i hi cc c trng c rt trch ra ca tnh hiu l cc c trng phi

    c xem l duy nht ca tnh hiu , trnh vic trng lp cc tn hiu mc d

    chng l hai tn hiu khc nhau lc u.

    Cc phng php bin i tn hiu c cp n trong Lun vn l

    MFCC v LPC l hai phng php kh ph bin, tuy chng vn cn tn ti nhng

    hn ch nhng khng th ph nhn s mnh m ca chng.

  • 31

    Chng III NHN DNG BNG M HNH MNG NEURAL

    I. Tng quan

    Mng neural nhn to l m hnh tnh ton da trn m phng hot ng ca

    no b con ngi. Trong nhng nm gn y, mng neural c quan tm pht

    trin v c ng dng vo cc h thng nhn dng ng, h thng d on v cc

    h thng iu khin t ng. Mng neural l h thng nhng c trng c hc t

    cc v d ch khng phi l c lp trnh nh mt thc bnh thng.

    Mng neural c th c chia thnh hai loi theo cu trc : mng truyn

    thng v mng hi quy.

    Mng truyn thng: trong mng ny, cc n ron c nhm li thnh cc

    lp. Tn hiu theo t lp ng vo v i n ng ra thng qua cc kt ni n

    hng. Cc t bo n ron c kt ni t lp ny n lp khc, nhng khng kt

    ni vi cc t bo trong cng mt lp.

    Mng hi quy: trong mng kin trc loi ny, cc t bo n ron u ra

    c php phn hi thng tin li cc t bo n ron ging n hay cc t bo trong

    cc lp song song vi n. Do , tn hiu c th theo c hai hng l truyn

    thng v truyn ngc. Mng hi quy c mt b nh ng, u ra ca chng phn

    nh ngay lp tc u vo hin ti cng nh u vo v u ra trc .

    Phn loi theo phng php hun luyn th c hai loi chnh l hun

    luyn c gim st v khng c gim st. Ngoi ra cn mt phng php th ba

    l hun luyn tng cng.

    Hun luyn c gim st: Thut ton hc gim st iu chnh thng s ca

    cc trng s u vo ca t bo n ron. Tp hun luyn bao gm mt tp hp cc

    mu u vo v cc kt qu u ra mong mun tng ng vi mu u vo. Cc

    mng nron iu chnh trng s lin kt ca n tm hiu mi quan h gia cc

    cp u vo - u ra. Mng nron c hun luyn thnh cng th c th h c

    s dng tm u ra ph hp nht i vi bt k u vo hp l.

    Hun luyn khng c gim st: Thut ton hun luyn khng c gim

    st khng yu cu u ra mong mun c bit trc. Trong khi hun luyn, ch c

  • 32

    tp mu u vo v mng t ng m phng nhng trng s cho cc kt ni theo

    tng cm tp mu trong nhm vi c trng tng ng.

    Hun luyn tng cng: Nh cc phng php trc , hun luyn

    tng cng l mt trng hp c bit. Thay v hun luyn ch cho chng u ra

    mong mun th thut ton hun luyn tng cng s dng ch mt nh ph bnh

    nh gi im tt nht ca mng neural.

    II. Qu trnh hot ng

    1) T bo ca mng

    Gii thch thng s:

    x1, x2, , xn: Cc tn hiu u vo (Input). C th l tn hiu cn nhn

    dng hoc tn hiu dng hun luyn.

    wj1, wji, wjn: L cc trng s (weights) ng vi tng ng vo xn.

    f(.) : Hm ngng (threshold function). C th l hm ngng n

    thun hay hm Xch ma hay hm tip tuyn Hyperbol hoc cng c th l

    hm radial.

    Mt s biu thc ca hm f:

    wj1

    f(.)

    x1

    xi

    xn

    wji

    wjn

    yj

    Hnh 3. 1 M hnh chi tit 1 t bo neural

  • 33

    Loi hm ngng Hm

    Hm tuyn tnh f(s) = s

    Hm ngng = +, > , <

    Hm Xch ma f(s) = 1/(1 + exp(-s))

    y(j): u ra ca tn hiu (Output) sau khi c hun luyn hay nhn dng.

    Cng thc tnh:

    = .

    =1

    Neuron ny s hot ng nh sau: gi s c N gi tr u vo xn, th

    neuron s c N trng s wjn tng ng vi N ng truyn u vo. Sau

    neuron s ly u vo th nht (x1), nhn vi trng s trn ng vo th nht

    (wj1), ly gi tr u vo th hai nhn vi trng s ca ng vo th hai v.v...,

    ri ly tng ca tt c cc kt qu thu c.

  • 34

    2) Mng Neural truyn thng nhiu lp

    a) M hnh c bn:

    Ch : y l m hnh gm 3 lp c bn: lp u vo, lp n v lp u ra. M hnh ch mang tnh cht minh ha, trn thc t s neuron c th nhiu hn hoc s lp n c th nhiu hn mt.

    b) Lut hc ca mng:

    Lut hc l mt th tc sa i cc trng s v h s hiu chnh ca

    mng neuron (Th tc ny cng c th c gi l mt thut ton hun luyn)

    Mc ch ca lut hc l hun luyn mng thc hin mt s nhim v. C

    nhiu loi lut hc hun luyn mng neuron. Chng gm ba loi chnh: lut hc

    c gim st, lut hc khng gim st v lut hc tng cng.

    Trong lut hc c gim st, lut hc a ra mt tp hp cc mu c quy

    tc v tng thch vi mng:

    {(x(k)

    , d(k)

    )} k = 1, 2, 3, .., p

    Hnh 3. 2 M hnh mng nhiu lp

  • 35

    x(k)

    l mt u vo mng v d(k) tng ng vi u ra mong mun.

    Khi cc u vo c p dng vo mng, cc kt qu u ra mng c so snh

    vi cc mc tiu. Lut hc sau c s dng iu chnh trng s (wjk) v h

    s hiu chnh ca mng dch chuyn u ra gn vi cc mc tiu hn.

    Lut hc khng gim st: trng s v h s hiu chnh c sa i

    p ng vi u vo mng. C mc tiu khng l u ra c sn. iu ny

    dng nh khng thc t. Lm th no bn c th hun luyn mt mng nu bn

    khng bit n phi lm g? Hu ht cc thut ton thc hin s hot ng phn

    cm. Chng c luyn phn loi cc m hnh u vo thnh mt s hu hn

    cc lp. iu ny c bit hu ch trong cc ng dng nh l lng t ha vector.

    Lut hc gia tng tng t lut hc c gim st, ngoi tr vic, thay

    v a ra cc u ra chnh xc cho mi u vo mng, thut ton ch cho mt lp.

    Lp l thc o cho s hot ng ca mng trn mt chui u vo. y l loi

    lut hc hin nay t ph bin hn so vi lut hc c gim st. N dng nh l

    ph hp nht kim sot cc ng dng h thng.

    Lut hc Adaline (Adaptive linear Element):

    wj = (d(k) wTx(k))xj(k)

    Lut ny cn c gi l lut hc Widrow-Hoff, hay cng c gi l

    lut LMS (Least Mean Square), lut hc ny c s dng cho mng n mt lp

    bao gm mt mng Adalines cn gi l mng tuyn tnh v Adaline c lp vi

    cc phn khc. Trong lut hc Adaline cc trng s c khi to vi mt gi tr

    bt k v c so snh vi cc trng s trong lut hc: wj = rx(t), tn hiu

    hc:

    r = d y = d - wTx

  • 36

    III. Qu trnh hun luyn

    1) Thut ton lan truyn ngc

    a) Khi nim v tng

    Biu thc thut ton hun luyn lan truyn ngc l mt thut ton quan

    trng nht trong lch s pht trin ca mng Neural. Thut ton ny c s dng

    trong mng truyn thng nhiu lp bao gm cc thnh phn x l vi hm lin

    tc kh vi. Nh nhng mng lin kt vi biu thc hc lan truyn ngc c gi

    l mng lan truyn ngc. Cho mt tp u vo-ra {(x(k), d(k))} k = 1, 2, 3, .., p,

    thut ton cung cp mt th tc thay i trng s sao cho mu tn hiu u vo

    ph hp. iu c bn cho biu thc cp nht trng s ny n gin ch l phng

    php gradient-descent (tin dn ti cc tiu a phng) c s dng cho mt

    Perceptron n vi thnh phn kh vi.

    Cho cp gi tr vo-ra mong mun (x(k), d(k)). Vi thut ton ny chng ta s

    c hai giai on cn biu din trn lu lng d liu. Th nht, mu u vo x(k)

    c lan truyn t lp vo cho ti lp ra, nh l kt qu ca lng d liu truyn

    thng. u ra y(k) nhn gi tr tht ca qu trnh lan truyn thng. Sau kt qu

    tn hiu sai s c a ra t s khc nhau gia u ra mong mun d(k) v u ra

    thc t y(k) v c lan truyn ngc li t lp ra ti cc lp trc n cp nht

    li cc trng s w.

    b) M hnh minh ha

    Hnh 1.1 m t kin trc c bn ca mt mng lan truyn ngc. Gm ba

    lp c bn: lp u vo, lp n v lp u ra. Tn hiu theo lp u vo lan

    truyn cho ti lp ra, sau xc nh c sai s da trn s khc nhau ca tn

    hiu ra mong mun v tn hiu ra thc t, t lan truyn ngc li cc lp iu

    chnh trng s u ra gn nht vi u ra mong mun.

  • 37

    Lan truyn ngc cc tn

    hiu sai s

    Lan truyn thng Lan truyn ngc

    Hnh 3. 3 M hnh tng qut 3 lp

    Trng s (wqm)

    Hnh 3. 4 M hnh chi tit c bn

    yi (i = 1, , n)

    Gi tr u ra

    Gi tr u vo

    xj (j = 1,.,m )

    Lp ng vo (Input layer)

    Lp n (Hidden layer)

    zq (q = 1,, g)

    Lp ng ra (Output layer)

  • 38

    Hnh 1.2 m t chi tit v thut ton lan truyn ngc, kt qu c th d dng

    m rng vi bt k lp no. Trong hnh 1.2, chng ta c m PE u vo ng vi m

    tn hiu u vo x, g PE lp n v n PE lp u ra tng ng vi n tn hiu ng ra

    y. Cc ng gch lin th hin tn hiu lan truyn theo hng thng (t lp vo

    n lp ra), ng gch t th hin tn hiu sai s c lan truyn ngc (t lp

    u ra v cc lp trc ).

    c) Tnh ton cc gi tr v tham s

    Cho mt mu gi tr u vo x th mt PE g lp n s nhn mt gi tr net u

    vo: (2.1)

    = .

    =1

    v gi tr u ra: (2.2)

    = = .

    =1

    Gi tr net u vo cho mt PE i trong lp ra: (2.3)

    = . =

    =1

    .

    =1

    =1

    v u ra thc t yi : (2.4)

    = = . =

    =1

    .

    =1

    =1

  • 39

    Cc biu thc trn y ch ra qu trnh lan truyn thng ca tn hiu ng vo

    i qua cc lp. Tip theo, chng ta s xem xt tn hiu li v lan truyn ngc

    chng.

    Biu thc tnh sai s: (2.5)

    () =1

    2

    2 = 1

    2 .

    =1

    2

    =1

    =1

    Trng s trong kt ni t lp n n lp ra c cp nht bng: (2.6)

    =

    S dng biu thc 2.3 2.5, chng ta c: (2.7)

    =

    =

    Khi l tn hiu sai s nt th i trong lp u ra. Biu thc ca tn hiu sai

    s: (2.8)

    =

    =

    Khi neti l net u vo n PE i ca lp u ra v a(neti) = a(neti)/ (neti).

    Kt qu ny ging tng t nh lut hc delta : (2.9)

  • 40

    =

    =

    ()

    ()

    ()

    ()

    cho mt PE lp n c u vo by gi l zq ca lp n.

    Vic cp nht trong s trong kt ni t u vo n lp n, chng ta s dng

    quy tc dy chuyn vi phng php gradient-descent (tin dn ti cc tiu a

    phng) v trng s c cp nht trn trng s kt ni PE j trong lp u vo n

    PE q trong lp n,

    =

    =

    =

    T biu thc (2.5), n r rng l mi sai s [di yi], i = 1, 2, , n l hm s ca

    zq. Chng ta c: (2.10)

    =

    =1

    Chng ta s dng vi cho biu thc 2.10: (2.11)

    = .

    =1

    =

    hq l tn hiu sai s ca PE q trong lp n v biu thc ca n l: (2.12)

    =

    =

    =1

  • 41

    Khi netq l net u vo n PE q ca lp n (2.1), tn hiu sai s ca PE trong

    lp n th khc vi tn hiu sai s ca PE trong lp u ra nh hai biu thc (2.8)

    v(2.12). V s khc nhau ny, th tc cp nht trng s trn c gi l lut hc

    delta tng qut. Tn hiu sai s hq ca mt PE lp n q c th c xc nh bi cc

    tn hiu sai s vi ca cc PE v yi, chng l ngun cung cp d liu. Nhng h s ch

    l nhng trng s c s dng cho vic lan truyn thng, nhng y chng l lan

    truyn ngc cc tn hiu li thay v lan truyn tn hiu theo ng thng. l cc

    ng gch t theo Hnh 1.2(M hnh chi tit c bn). iu quan trng ca biu

    thc cp nht - lan truyn ngc l vic tnh ton s thay i trng s cho mt kt

    ni, chng ta ch cn mt cp tn hiu c sn c hai u ca kt ni.

    Vi s lp ty , lut cp nht lan truyn ngc s c dng tng qut nh sau:

    = = . (2.13)

    Khi u vo j v u ra i l hai u ca kt ni t PE j n PE i, xj l gi tr

    u vo t mt PE lp n hay u vo t bn ngoi, i l tn hiu hc m chng ta

    xc nh n ti biu thc 2.8 cho nhng trng s kt ni ca lp u ra v biu thc

    2.12 cho tt c cc lp khc. Khi hm sigmoid lng cc c s dng nh l hm

    kch hot v sau s dng biu thc 2.x th biu thc 2.8 v 2.12 tr thnh:

    =

    =

    1

    2 1 2 2.

    =

    =

  • 42

    v

    =

    =

    =1

    d) Cc bc xy dng thut ton

    Xt mt mng gm Q lp truyn thng, q = 1, 2, , Q, qneti v qyj biu din

    net u vo v u ra ca n v th i trong lp th q. Mng ny c m im u

    vo v n im u ra. qwij s biu din trng s kt ni t q-1

    yj n qyi.

    u vo: a vo mt tp cc cp hun luyn {(x(k) , d(k))| k =1, 2, , p},

    khi vector u vo c tng ln vi phn t cui cng l -1 , tc l =1()

    = 1.

    Bc 0: Khi to

    Chn > 0 v Emax (sai s chp nhn c). Khi to trng s

    gi tr ngu nhin nh nht v t E=0, k=1.

    Bc 1: Vng hun luyn

    p dng mu ng vo th k cho lp ng vo (q =1)

    qyi =

    1yi =

    () cho tt c i

    Bc 2: Lan truyn thng

    Lan truyn tn hiu thng thng qua mng s dng biu thc:

    =

    =

    . 1

    =1

    Gi tr ca i v q chy ti khi cc ng ra ca lp cui cng Qyj

    c xc nh

    Bc 3: o c sai s ng ra

  • 43

    Tnh ton gi tr sai s v nhng tn hiu sai s Qi cho lp ng ra:

    =1

    2

    ()

    2

    +

    =1

    (Ch : Cng dn sai s)

    = ()

    Bc 4: Lan truyn ngc sai s

    Lan truyn ngc nhng tn hiu sai s cp nhp nhng

    trng s v tnh ton nhng tn hiu sai s q-1i cho nhng lp trc:

    =

    1

    = +

    1 = 1

    .

    = , 1, , 2

    Bc 5: Mt chu k lp:

    Kim tra ton b tp hun luyn trong vng lp thc hin.

    Nu k < p, th k = k + 1 v quay li bc 1. Ngc li ta chuyn sang

    bc 6.

    Bc 6: Kim tra tng sai s

    Kim tra tng sai s ng ra, nu E

  • 44

    2) M phng trn Matlab v ng dng vo nhn dng ting ni

    Ni dung m phng: Hun luyn mng Neural chuyn i th hnh tam

    gic sang hnh Sin.

    tng: Xy dng cc cp d liu: u vo m n c dng m phng

    th dng tam gic v u ra tng ng s l m phng th hnh sin.

    a) th hnh Tam gic b) th hnh sin

    Xy dng chng trnh:

    N = 100;

    for i=1:N

    t(i)=i*2*pi/N;

    end

    d = sin(t);

    for i=1:N

    if i

  • 45

    end

    x2(1)=0;

    for i=2:N

    x2(i)=x1(i-1);

    end

    plot(t,x1,'black'); % v hnh tam gic

    p=[x1;x2];

    net = newff(p,d,3);

    y=sim(net,p);

    net.trainParam.epochs = 200;

    net.trainParam.goal = 0.001;

    net = train(net,p,d);

    y = sim(net,p);

    for i=1:N

    t(i)=i*2*pi/N;

    end

    d = sin(t);

    for i=1:N

    if i

  • 46

    Kt qu:

    Tn hiu ng ra mong mun d

    Tn hiu u ra thc t y

    Hnh 3. 7 th dng tam gic (xi)

    Hnh 3. 6 Hnh minh ha qu trnh hun luyn

  • 47

    Hnh 3. 8 Mng Neural s dng

    ng dng vo nhn dng ting ni:

    Cho mng Neural nhiu lp truyn thng, trong qu trnh hun luyn v

    nhn dng ty vo chnh xc v tc nhn dng s iu chnh li s lp n v

    s t bo neuron trong mng.

    Sau qu trnh x l tn hiu v rt trch c trng ta thu c cc ma trn

    c trng ca tnh hiu ban u:

    1 1

    Vi n s lng c trng, ma trn ny l ma trn c dng vo hai vic: C

    th l dng n hun luyn mng hay n l tn hiu cn nhn dng.

    Th nht, vic dng ma trn c trng hun luyn mng.

    Phng php hun luyn ngh s dng l phng php lan truyn ngc.

    V ta c n c trng nn u vo s c n ng, v lc ny cp d liu mong mun

    s l (xn , yn) tng ng u vo xn v u ra mong mun yn

    Cc bc hun luyn:

    Bc 0: Khi to

    Chn > 0 v Emax (sai s chp nhn c). Khi to trng s

    gi tr ngu nhin nh nht v t E=0, k=1.

  • 48

    Bc 1: Vng hun luyn

    p dng mu ng vo th k cho lp ng vo (q =1)

    qyi =

    1yi = x(k)

    i

    Bc 2: Lan truyn ti

    Tn hiu x trong ma trn c trng s c a vo ng vo ca

    mng Neural. V tn hiu c lan truyn thng qua tng lp ca

    mng cho ti lp cui cng. Tn hiu u ra tun theo hm:

    =

    =

    . 1

    =1

    Gi tr ca i v q chy ti khi cc ng ra ca lp cui cng Qyj c

    xc nh, c u ra nh mong mun th chng ta cn t mt

    hm hp l ti y. Trng s chn ban u l nh nht cho mng, sau

    qu trnh cp nht li trng s th n s c thay th bng trng s

    mi.

    Bc 3: o c sai s: ti bc ny sai s s c tnh ton c th

    cp nht li cc trng s cho mng.

    Bc 4: Lan truyn ngc sai s: Lan truyn ngc nhng tn hiu sai

    s cp nhp nhng trng s v tnh ton nhng tn hiu sai scho

    nhng lp trc

    Bc 5: Chu k lp: Kim tra s neuron trong mng tnh ton ht

    cha, nu cha th quay li Bc1 nu tnh ton ht th qua Bc 6.

    Bc 6: Kim tra tng sai s ng ra. Nu E

  • 49

    Trn y l tm lc cc qu trnh c bn cho bi ton lan truyn ngc

    dnh hun luyn tn hiu theo mu ma trn c trung ban u. Nh vy, kt

    thc qu trnh ta s c kt qu l khi a mt tn hiu u vo tng t nh tn

    hiu u vo ca mng th u ra s l kt qu mong mun (y).

    Th hai, nhn dng tn hiu vi cc ma trn c trng ban u:

    Ma trn c trng ng vi mt tn hiu no cn nhn dng c

    a vo mng, thng qua qu trnh lan truyn thng, tnh ton th mng s cho ra

    mt kt qu tng ng, nu kt qu tha u ra mong mun (c sai s nh

    gi ng) th chng ta chn u ra mong mun.

  • 50

    IV. Kt lun

    Ngoi nhng thnh cng ca gii thut hc lan truyn ngc, vn cn c

    mt s kha cnh lm cho gii thut tr nn cha c bo m l mi lc u tt.

    Kh khn ch yu l qu trnh hun luyn lu. C th do nhp hc v ng lc

    khng ti u. S sai st trong vic hun luyn ni chung xut hin t hai ngun

    mng lit v nhng cc tiu a phng.

    Mng lit xy ra khi nhng trng s c iu chnh ti nhng gi tr rt

    ln. Bi v s h dc, mng c th b mc by ti mt cc tiu a phng khi

    c nhiu cc tiu thp hn gn bn cnh. Nhng phng php thng k c th gip

    trnh ci by ny, nhng chng lm chm. Mt phng n khc l tng thm s

    lng n v n. Nh vy s lm vic trong khng gian sai s nhiu chiu, nn c

    hi gp by nh hn. Tuy nhin vic tng cng c gii hn trn, khi vt qua gii

    hn ny, c hi mc by li tng ln.

  • 51

    KT LUN

    Sau qu trnh nghin cu nhn dng ging ni, lun vn lm c mt s

    cng vic sau:

    a ra mt ci nhn tng quan v nhn dng ging ni.

    X l tn hiu m thanh v a ra mt s phng php rt trch

    cc c trng ca tn hiu.

    Nghin cu phng php nhn dng s dng mng Neural, v

    phng php hun luyn lan truyn ngc.

    Trong gii hn thi gian v sc lc ca mt ngi, em mi ch c khi u

    tip cn nghin cu v nhn dng ting ni, v vy chc chn trong lun vn cn

    nhiu thiu st, so vi s pht trin nhn dng th cc kt qu t c trong lun

    vn khng ng k, nhng em mong rng lun vn ny s gp mt phn vo vic

    thc y nghin cu v ng dng ca h nhn dng ting ni.

    Hng pht trin: kim nghim v cc u im cng nh khuyt im

    m mng Neural, phng php hun luyn cng nh cc qu trnh rt trch c

    trng th em mong mun n c ng dng thc t vo cc h thng thng minh,

    h thng nhn dng ting ni, h thng iu khin bng ting ni. V gn hn l

    ng dng vi h thng nhn dng ngn ng ting Vit. V trc mt th ng dng

    vi cc chng trnh m phng c ci nhn rng hn v c im ca chng.

  • 52

  • 53

    TI LIU THAM KHO:

    [1] Homayoon Beigi, Fundamentals of Speaker Recognition, Springer Science

    Business Media, 2011

    [2] C.T.Lin & C.S.G.Lee, Neural fuzzy system

    [3] F.J.Owens, Signal Processing of Speech, Printed in Hong Kong

    [4] Duc Truong Pham and Liu Xing, Neural networks for Identification,

    Prediction and Control, Printed in Great Britain

    [5] Roberto Pieraccini, The Voice in the Machine, Printed and bound in the

    United States of America.

    [6] PGS.TS Nguyn Hu Phng, X L Tn Hiu S, Nh Xut Bn Thng

    K, 09/2003

    [7] Quch Tun Ngc, X L Tn Hiu S, Nh Xut bn Gio Dc, 04/1998