An efficient algorithm for pitch determination of speech signals-Kalman filter approach

2006-04-19
Salor, Ozgul
DEMİREKLER, MÜBECCEL
Orguner, Umut
In this paper, an efficient algorithm for pitch determination of speech signals is presented. Pitch period of speech signals does not contain sharp changes in time in voiced and voiced-unvoiced transition regions. Depending on this property, Kalman Filter has been used to estimate the pitch period similar to the way it is used in the target tracking problems. The measurement for the Kalman Filter is obtained by using the integer pitch calculation based on autocorrelation method, which is used as the first step of pitch determination in MELP speech coding algorithm. Kalman Filter makes an a priori estimate, which depends on the general behavior of the pitch period in time and this estimate is updated using this measurement to obtain an a posteriori estimate. The proposed method provides a reduction in the computational complexity since the autocorralation search is made only inside the gating volume of the Kalman Filter. Therefore, the proposed method does not require any pitch doubling check. It also does not need any fractional pitch computations. The pitch periods obtained using this method have been compared to those determined in MELP algorithm and it has been observed that comparible results have been obtained.

Suggestions

Wireless speech recognition using fixed point mixed excitation linear prediction (MELP) vocoder
Acar, D; Karci, MH; Ilk, HG; Demirekler, Mübeccel (2002-07-19)
A bit stream based front-end for wireless speech recognition system that operates on fixed point mixed excitation linear prediction (MELP) vocoder is presented in this paper. Speaker dependent, isolated word recognition accuracies obtained from conventional and bit stream based front-end systems are obtained and their statistical significance is discussed. Feature parameters are extracted from original (wireline) and decoded speech (conventional) and from the quantized spectral information (bit stream) of t...
Optimum placement of microphone array for sound capture using genetic algoritms
Birinci, Isil Yazgan; Leblebicioğlu, Mehmet Kemal (2006-01-01)
This paper presents a new method based on genetic algorithm for the optimum placement of microphone arrays for high-quality sound pickup. Microphone arrays are being used for the purposes of direction-of-arrival estimation and tracking of sound sources [1][2] as well as high quality sound capture by focusing on a source [3]. The placement of microphones has direct effect on the sound quality acquired [4][5]. The method proposed in this paper uses a metric function that takes this effect into account and op...
Signature Based Vegetation Detection on Hyperspectral Images
Özdemir, Okan Bilge; Soydan, Hilal; Çetin, Yasemin; Düzgün, Hafize Şebnem (2015-05-19)
In this study, the contribution of utilizing hyperspectral unmixing algorithms on signature based target detection algorithms is studied. Spectral Angle Mapper (SAM), Spectral Matched Filter (SMF) and Adaptive Cosine Estimator (ACE) algorithms are selected as target detection methods and the performance change related to the target spectral acquisition is evaluated. The spectral signature of the desired target, corn, is acquired from ASD hyperspectral library as well as from the hypespectral unmixing endmem...
Robust Attitude Estimation Using IMU-Only Measurements
Candan, Batu; Söken, Halil Ersin (2021-01-01)
© 1963-2012 IEEE.This article proposes two novel covariance-tuning methods to form a robust Kalman filter (RKF) algorithm for attitude (i.e., roll and pitch) estimation using the measurements of only an inertial measurement unit (IMU). KF-based and complementary filtering (CF)-based approaches are the two common methods for solving the attitude estimation problem. Efficiency and optimality of the KF-based attitude filters are correlated with appropriate tuning of the covariance matrices. Manual tuning proce...
Online state estimation for discrete nonlinear dynamic systems with nonlinear noise and interference
Demirbaş, Kerim (2015-01-01)
This paper presents a real-time recursive state filtering and prediction scheme (PR) for discrete nonlinear dynamic systems with nonlinear noise and random interference, such as undesired random jamming or clutter. The PR is based upon discrete noise approximation, state quantization, and a suboptimal implementation of multiple composite hypothesis testing. The PR outperforms both the sampling importance resampling (SIR) particle filter and auxiliary sampling importance resampling (ASIR) particle filter; wh...
Citation Formats
O. Salor, M. DEMİREKLER, and U. Orguner, “An efficient algorithm for pitch determination of speech signals-Kalman filter approach,” 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/47296.