Abstract:

Objectives: The existing linear prediction (LP) formant estimation algorithms are difficult to locate formant precisely because of the pseudo root interference and interaction between poles.Because of the low order fitting formant of LP prediction,the accuracy of formant extraction is fundamentally limited.It is difficult to remove false roots and spectrum aliasing caused by pole interaction in the formant extraction of high-order LP.In order to solve the problem of large error of LP formant detection,a formant estimation algorithm based on high-order LP coefficient root value screening was proposed. The root determination threshold, optimal LP root value distribution, peak distribution of formant in spectral envelope and formant estimation error of speech digital resonance model constraints under different orders are investigated.

Methods: The value of LP order is increased to improve the fitting degree of LP system spectrum of speech signal.The calculation precision of formant frequency of speech signal is analyzed in different order,and the root value of linear system with higher linear peak fitting precision is obtained.A speech digital resonance model is used to constrain the root amplitude range of the formant, and the number of false roots is reduced by matching the root amplitude of the order to filter the root values of the linear system.Combined with power weighting,the main spectral components of the signal are weighted. So the amplitude of speech frequency is corrected, and the energy matching between the spectral peak of the speech signal and the spectral peak of LPC is enhanced, the distance between poles is extended, the prediction error caused by harmonic generation interference is reduced, and the peak frequency discrimination of spectrum is improved.

Results: As can be seen from the algorithm structure, the speech signal is preprocessed, in which the low frequency information is reweighted to reduce the interference of fundamental frequency to formant detection.And the high frequency information is enhanced to increase the amplitude distinction of the third formant in the high spectrum line. And the end detection is isolated to do the high-order LP analysis of the spoken frame under the constraint of digital resonance model. The model includes three main techniques which improving the performance:(1) Within the system tolerance range, LP order is increased, which can improve the formant prediction accuracy. The formant is the peak frequency of the spectral envelope, which corresponding to the zero-pole of the LP polynomial. The 9-order linear prediction only preserves the basic shape of LP response amplitude spectrum of speech signal.When the order of LP is increased to the 15,the fitting degree of the signal is increased,and the zero and pole of LP is dense and the distribution of LP is closer to the unit circle.The 15th order LP compensates for the sacrifice of formant fitting accuracy caused by the 9th order linear fitting, which improves the formant extraction accuracy by 2.5%. (2) Using the threshold value under the constraint of digital resonance root value to determine the complex roots,the low frequency false roots generated by fundamental frequency harmonics and the false roots generated by formant harmonics is effectively filtered.The zeroes-poles of the LP polynomial are the complex roots corresponding to the formant peaks.In the view of the distribution of formant detection root values, the high-order LP root threshold constrained by digital formant root values can effectively filter the false roots generated by harmonic action of sound channel. And accurately the location of the root corresponding to formant root values in the unit circle is accurately located. (3) The revised signal prediction formant is more accurate by reweighting the speech frequency power.The spectrum envelope energy is more concentrated after power weighting.At order 18, the aliasing interference caused by the peak frequency of the formant at 1363Hz to 1359Hz is eliminated. In terms of the robustness of the algorithm and the overall performance comparison of different methods,the proposed algorithm can extract the formant robustly from order 9 to 22, and the model algorithm shows the optimal performance when the formant is extracted from order 18.

Conclusions:The method of formant detection based on LPC is improved.The effect of improving the order of linear prediction on formant extraction was studied.Aiming at the problem of multiple pseudo-roots and multi-pole interaction caused by increasing the order of linear prediction, the error of formant extraction constrained by the speech-digital resonance model is minimized. The relationship between the order of linear prediction and the screening threshold of root amplitude was analyzed. To remove false roots, the root amplitude feedback method under digital resonance constraint was used to obtain the filtering threshold of matching high order and low error rate. Combined with the power weighting, amplitude of the peak of the prominent spectrum is strengthened,which eliminates the pole interaction in formant extraction,achieving accurate and effective formant extraction.

Key words: linear prediction, digital resonance, power weighting, formant