An Improved Spectral Subtraction Algorithm for Speech Enhancement System. Shun Na, Weixing Li, Yang Liu*

Transcription

1 6h Ieraioal Coferece o Iformaio Egieerig for Mechaics ad Maerials (ICIMM 16) A Improved Specral Subracio Algorihm for Speech Ehaceme Sysem Shu Na, Weixig Li, Yag Liu* College of Elecroic Iformaio Egieerig, Ier Mogolia Uiversiy, Hohho, 11, Chia * Correspodig auhor: address: yagliuimu@163.com Keyords:speech ehaceme, specral subracio, oise esimaio. Absrac I his paper, e prese a applicaio of specral subracio (SS) algorihm i speech ehaceme sysem o exrac he pure speech sigal as far as possible. I coras o he exisig research, he proposed algorihm improves he voice qualiy, hich reduces speech disorio, elimiaes backgroud oise ad improves he speech ielligibiliy. This paper firs iroduces he research sigificace of he speech ehaceme, he iroduces he releva heories of speech sigal processig, ad expouds he basic specral subracio speech ehaceme, hrough a lo of simulaio experimes verify he effec of specral subracio. Based o he voice acivaio deecio algorihm is sudied ad a improved specrum subracio ISS algorihm as preseed. Our simulaio resuls sho ha he proposed ISS Algorihm is effecive ih he loer compuaioal complexiy i speech ehaceme sysem. 1. Iroducio There are may siuaios he speech has o be processed i he presece of udesirable backgroud oise ha degrades speech qualiy ad ielligibiliy. A variey of speech ehaceme mehods capable o reduce backgroud oise ere sudied i he lieraure. Evirome oise ieviably iflueces our speech commuicaio qualiy. Speech ehaceme echology is a available approach o resolve he ifluece of oise, hile egieers are i favour of sigle microphoe speech ehaceme echology based o shor ime specral esimaio, such as algorihms of specral subracio [1], Wieer filer [], miimum mea square error(mmse) esimaio [3], vecor Taylor Series[4] ad cepsral hisogram equalizaio [5] ec. These algorihms improve he ehaceme effec o a cerai exe, bu he ehaceme effec is sill o be improved. Tha is because hese algorihms have o cocered ih he ulimae propery of oise specral. Specral subracio mehod, as proposed by [6], is a commoly used oise reducio mehod ha has high oise reducio performace. The basic priciple of he specral subracio mehod is o subrac he shoe-erm specral magiude of oise from ha of he oisy speech. The oise is assumed o be ucorrelaed ad addiive o he speech sigal. A esimae of he oise sigal is measured durig silece or o-speech aciviy i he sigal. Specral subracio from he voice of he shor-erm specrum ih oise value mius he oise i he shor-erm specrum o achieve he purpose of he speech ehaceme, i adoped by he algorihm is simple ad easy o impleme. The mai idea of he specral subracio is assumig ha oise ad speech sigal uder he codiio of idepede of each oher, from he bad oise poer specrum mius he oise poer specrum, relaively pure speech specrum is obaied, he folloig is he basic priciple of specrum subracio.. Discussed problems Hypohesis y ( ) is oise speech sigal, s( ) is pure speech sigal, ( ) deoes sigal o oise. The voice is shor ime smoohly, so ha i is i shor-erm specral magiude esimae saioary 16. The auhors - Published by Alais Press 318

2 radom sigal, assumig ha oise is () ad voice s () [7], addiive oise. Ge sigal addiive model y () = s () + () (1) Eergy specrum of speech sigals ih oise ca be expressed as afer dealig ih he add ido of he sigal, FFT rasform respecively is y (), s (), (), here are y() = s() + () () Afer dealig ih he add ido Fourier rasform (FFT) sigal Y( ) = S( ) + N( ) (3) Poer specrum is Agai o ype available, Because of he assumpios are () ad voice S( ω) Y ( ) = S ( ) + N ( ) * + Re S( N ) ( ) ) ( ( ) ) = ( ( ) + ( ( ) ) E Y E S E N s () * { } + E Re S( N ) ( ) (4) (5) are idepede of each oher, N ( ω) ad is also idepede of each oher, accordig o he characerisics of saioary radom * N ω E is a zero mea Gaussia disribuio. So he expressio of { Re S( N ) ( ) } oise ( ) Therefore, (3-5) deformaio for For he frame iside shor ime saioary process here Y ( ) is, ) ( ( ) ) ( ( ) ( ( ) ) is, E Y = E S + E N (6) Y ( ) = S ( ) + N ( ) (7) N 1 π k j N jφ ( ) (8) = Y ( ) = ye ( ) = Y( ) e here φ( ) is he phase of oise speech of Y ( ). Because direcly by oise speech oise eergy specrum cao esimaed i N ( ), geerally several frames sile phase oise sigal eergy specrum of he oise poer specrum esimae N ( ) is calculaed. Due o he poer specrum of smooh voices i voice before ad afer ca be hough of as basic did o chage, so e ca hrough he voice of so-called ave silece before o esimae he oise poer specrum { ps( ) = py ( ) p( ) (9) Such reducio ca be hough of as he poer specrum of he relaively pure speech, hoever, from he poer ca be resored afer oise reducio of speech sigal. I he cocree operaio, i order o preve he egaive poer specrum, specral py ( ) < p( ) reducio,to ps ( ) =, i.e., full specrum reducio compuaio formula is: ps( ) = py( ) p( ), py( ) p( ) (1) For assumpios ere o associaed ih he oise ad speech sigal, eergy specrum esimaio for speech S ( ) = Y ( ) N ( ) (11) ˆ here clea speech poer specrum esimae S ( ) by he eergy specrum of speech sigals ih oise mius, hich amed he oise poer specrum esimaio. Because of he oise poer specrum esimaio ad oise i he speech sigals ih oise exis differeces, eergy specrum of (1) may be egaive, i order o avoid he egaive eergy specrum, he egaive value is se o zero, his process is called half-ave recifier (or half ave recificaio). Through he half-ave recifier, pure voice eergy specrum esimaio ca be expressed as Sˆ ( ). 319

3 ˆ ˆ ˆ ( ) S ( ) S > S ( ) = (1) ˆ S ( ) < Combiig ih oise speech phase iformaio, hrough he iverse discree Fourier rasform (IDFT), ge clea speech sigal esimaio of sigal is ˆ( ) s ˆ j ( ) IDFT s ˆ( ) = ( S ( ) e φ ) (13) Specral subracio i he frequecy domai ill ake oise poer specrum mius he oise poer specrum, i order o ge clea speech poer specrum esimaio, prescribig afer ge speech specral ampliude esimaio, ih he phase oise o approximae he phase of he pure voice. Agai he iverse Fourier rasform for USES o resore ime domai sigals, flo char of specrum subracio speech ehaceme algorihm is sho i Figure Improved specrum subracio algorihm Fig.1: Specral subracio speech ehaceme algorihm The basic problems exisig abou he radiioal specral subracio algorihm [8], [9], is ha he ieviable music oise is iroduced. Accuraely esimae of oise i he speech sigals is eed ih oise specrum, i order o effecively filer ou he oise of he voice sigals. Noise specrum esimaio is more accurae, ehacig he smaller music oise i he sigal specrum. Hoever, because oise specrum ca be obaied direcly i he vas majoriy of specral subracio algorihm, hich is obaied by he eighed average of sile phase oise specrum esimaio. A resul of oise specrum esimaio error is he egaive eergy value. The egaive ih halfave recifier or full ave recifier (as se o he absolue value). I is o correc rea such misake, resulig furher disorio i he ime domai. I he ime domai, sigals are geeraed o ehace, he phase of speech sigals ih oise did o make ay chages. This is based o he fac ha he phase disorio of he effecs o he voice qualiy declie. Whe he sigal-o-oise raio (SNR) ha high (> 5 db), phase disorio is lile impac o he qualiy of voice, hoever, he he lo SNR (< db) he voice qualiy declie due o phase disorio ca be fel. The radiioal oise esimaio is based o he opimal smoohig ad leas saisical oise esimaio, hich he algorihm ih he improved oise esimaio based o voice aciviy deecio [1].Voice acivaio deecio refers o he voice from he speech sigal coais cerai sarig poi ad ed poi, also ko as he edpoi deecio. The purpose of speech edpoi deecio is from he coiuous recordig of he speech sigal ih oise isolaed useful speech sigal. Voice acivaio deecio is eed i he various speeches processig, ad is a impora lik. Accuraely deermie he begiig ad ed of ipu speech ill esure he performace of he voice processig sysem [11]. Fig.: Voice acivaio deecio block diagram Specific shor ime eergy deecio algorihm based o sigal is follos: i) Calculae each frame of speech eergy: 3 N 1 E = x ( m) (14) m=

4 here N is he frame legh, is he serial umber of he frame, m is each poi i each frame, 1 L, L is he umber of frames. I has a defec, hoever, ha is sesiive o high level (sigal of quadraic calculaio). For his purpose, he defiiio of shor ime average magiude fucios o characerize a frame of speech sigal eergy size, defiiio. ii) Average oise eergy calculaed before frames iii) Eergy maximum ad miimum value deoe EAX ad EMI iv) Accordig o he (15), deermie he hreshold. 4. Simulaio resuls N 1 M = x ( m) (15) m= T = mi[.3( EAX EMIN ) + EMN,4 EMN ] (16) Simulaio respecively he dra he origial clea speech aveform, specrum ad afer high-pass filer he speech sigal aveform ad specrum. The origial speech sigal aveform afer samplig i ime domai ad specrum graph, afer addig oise sigal plus oise speech sigal aveform ad specrum diagram. The basic specral subracio is simulaio as aveform diagram. Fig.3: Clea speech sigal I ca be see from he Fig.3, his aricle MATLAB has read he seleced voice sigal soud clearer a he high SNR. I fac, his sigal experimeal coras effec is o obvious. So before you elimiae oise experimes, e arificially add radom hie Gaussia oise o he origial sigal ad reduce he SNR of speech sigal. To image coras ca be see from he Fig.4, add Gaussia radom oise i pure speech sigal, he sigal aveform becomes relaively vague ad specral chage is also very obviously. The iroducio of radom oise sigal, grealy reduces he sigal-o-oise raio of speech sigals, his sep is o prepare for furher sudy o he back. Fig.4: Speech sigal ih oise 31

5 Origial speech aveform Number of sample 1 4 Speech aveform of add oise Number of sample 1 4 Ehaced voice aveform Number of sample 1 4 Fig.5: The realizaio of he basic specral subracio speech aveform The basic specral subracio ca be see from he Fig. 5, hich before ad afer implemeaio. The origial speech aveform is relaively smooh ad clear, afer joiig he oise speech aveform is blurry, obviously afer he classic specral subracio. Afer deducig he specrum of oise reducio of aveform is compared ih he origial pure voice. The basic back o he origial voice clariy, so i is proves ha he specral subracio is o realize he voice sreghe he use of a very good ool hrough he basic specral subracio pracice [1]. Based o he improved origial speech sigals aveform figure, add oise speech sigal aveform ad speech o sreghe afer he aveform diagram sho i Fig.6. Accordig o he above aalysis, e ca coclude ha he oise esimaio algorihm based o voice aciviy deecio afer he simulaio aveform is beer ha he classic basic specral subracio resulig from he simulaio aveform. Origial speech aveform Number of sample 1 4 Speech aveform of add oise Number of sample 1 4 Ehaced voice aveform Number of sample 1 4 Fig.6: Noise esimaio based o voice aciviy deecio algorihm simulaio 5. Coclusios This paper geeralizes he classic specral subracio for speech ehaceme sysem. The goal of his aricle is ry o remove he ierferece of oise o resore a pure voice, such as speech sigal acquisiio, exrac he oise from he speech sigal ad impleme o remove oise from he speech sigal. We leared some releva characerisics of sigal ad oise of esimaio i ime domai ad frequecy domai. We firs research speech o sreghe from he classic specral subracio. O he basis of he foud some shorages exisig i he radiioal specral subracio, e pu forard ad research a e modified specral subracio algorihms. Our aalysis ad simulaio idicae ha he performace of his improved algorihm is much beer ha ha of sadard specral subracio. 3

6 Ackoledgemes The auhors are graeful o he Naioal Sciece Foudaio of Chia for is suppor of his research. This ork is parly suppored by he Naioal Sciece Foudaio of Chia uder Gra 61367, ad , ad he Naural Sciece Foudaio of Ier Mogolia Auoomous Regio of Chia uder Gra 16MS64. Refereces [1] Sui, L, Zhag, X, Huag, J, Zhou, B, A improved specral subracio speech ehaceme algorihm uder o saioary oise. 11 Ieraioal Coferece o Wireless Commuicaios ad Sigal Processig (WCSP), IEEE, 11. [1] Zhag, B, The algorihm research of speech ehaceme based o avele. Harbi: Harbi Egieerig Uiversiy, 199. [3] Gupa, V. K., e al., Speech Ehaceme Usig MMSE Esimaio ad Specral Subracio Mehods. 11 Ieraioal Coferece o Devices ad Commuicaios (ICDeCom), IEEE, 11. [4] Yog, L, Zhe, W, Robus Speech Recogiio Based o Vecor Taylor Series. Joural of Tiaji Uiversiy, (3), PP.13-18, 11. [5] Zhao, Y, Jiag, B, Sraded Gaussia mixure hidde Markov models for robus speech recogiio. 1 IEEE Ieraioal Coferece o Acousics, Speech ad Sigal Processig (ICASSP), IEEE, 1. [6] Boll, S. F, Suppressio of acousic oise i speech usig specral subracio, IEEE Tras. o Acousics, Speech ad Sigal Processig, 7(7), pp , [7] Boll, S. F, Suppressio of acousic oise i speech usig specral subracio, IEEE Tras. o Acousics, Speech ad Sigal Processig, 7(7), pp , SOON, I. Y, KOH S. N, Speech ehaceme usig -D Fourier rasform. IEEE Tras Speech Audio Process, 1l(6), pp , 3. [8] Kamah, S, Loizou, P, A muli-bad specral subracio mehod for ehacig speech corruped by colored oise, Proc. of IEEE I. Cof. o Acousics, Speech ad Sigal Processig,. [9] Zhag, C, Hu, X, Zhou, Y, Specral subracio based o he srucure of oise poer specral desiy, ACTA ACUSTICA, 35(), pp.16-, 1. [1] ZCheg, G, Guo, L, Zhao, T, He, S, A More Effecive Speech Ehaceme Algorihm uder No-Saioary Noise Evirome, Joural of Norheser Polyechical Uiversiy, 8(5), pp , 1. [11] Kamah, S, Loizou, P, A muli-bad specral subracio mehod for ehacig speech corruped by colored oise, Proc. of IEEE I. Cof. o Acousics, Speech ad Sigal Processig,. Ioue, T, Saruaari, H, Takahashi, Y, Shikao, K, Theoreical aalysis of ieraive eak specral subracio via higher-order saisics, Proc. MLSP 1, pp. 5, 1. [1] Zhag, C, Hu, X, Zhou, Y, Specral subracio based o he srucure of oise poer specral desiy, ACTA ACUSTICA, 35(), pp.16-, 1. Takahashi, Y, Saruaari, H, Shikao, K, Musicaloiseaalysisimehodsofiegraigmicrophoearrayadspecral subracio based o higher-order saisics, EURASIP J. Adv. Sigal Process, 11, 1. 33