Pitch estimation of noisy speech signals using empirical mode decomposition

نویسندگان

  • Md. Khademul Islam Molla
  • Keikichi Hirose
  • Nobuaki Minematsu
  • Md. Kamrul Hasan
چکیده

This paper presents a pitch estimation method of noisy speech signal using empirical mode decomposition (EMD). The normalized autocorrelation function (NACF) of the noisy speech signal is decomposed into a finite set of band-limited signals termed as intrinsic mode functions (IMFs) using EMD. The periodicity of one IMF is supposed to be equal to the accurate pitch period. A conventional autocorrelation based pitch period detection method is used to select the IMF with pitch period. The accurate pitch period is obtained from the selected IMF. The pitch estimation performance in term of gross pitch error (GPE) of the proposed algorithm is compared with recently proposed methods. The experimental results show that the EMD based algorithm performs better in pitch estimation of noisy speech.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Empirical Mode Decomposition for Advanced Speech Signal Processing

Empirical mode decomposition (EMD) is a newly developed tool to analyze nonlinear and non-stationary signals. It is used to decompose any signal into a finite number of time varying subband signals termed as intrinsic mode functions (IMFs). Such data adaptive decomposition is recently used in speech enhancement. This study presents the concept of EMD and its application to advanced speech signa...

متن کامل

Non-stationary acoustic objects as atoms of voiced speech

In spite of the undisputedly high degree of non-stationarity of speech signals, the present day determination of its acoustic features is based on the assumption that speech production can be described as a linear time invariant (LTI) system on the time scale of about 20 ms [1]. In automatic speech recognition, the wide sense stationarity of an LTI– system is used as prerequisite for the consis...

متن کامل

In-car Speech Enhancement Using Ensemble Empirical Mode Decomposition

The performance of the human-machine dialogue at in-car environment is considerably deteriorated by background noises and other disturbances. In this paper, the authors present an in-car speech enhancement (ICSE) method to improve quality of speech signals suffering the in-car noises. The method is based on a novel signal processing technology called the ensemble empirical mode decomposition (E...

متن کامل

Empirical Mode Decomposition based Adaptive Filtering for Orthogonal Frequency Division Multiplexing Channel Estimation

This paper presents an empirical mode decomposition (EMD) based adaptive filter (AF) for channel estimation in OFDM system.  In this method, length of channel impulse response (CIR) is first approximated using Akaike information criterion (AIC). Then, CIR is estimated using adaptive filter with EMD decomposed IMF of the received OFDM symbol. The correlation and kurtosis measures are used to sel...

متن کامل

Robust pitch estimation in noisy speech using ZTW and group delay function

Identification of pitch for speech signals recorded in noisy environments is a fundamental and long persistent problem in speech research. Several time domain based techniques attempt to exploit the periodic nature of the waveform using autocorrelation function and its variants. Other set of techniques utilize the harmonic structure in the spectral domain to identify pitch values. Either of the...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007