Method and apparatus for pitch determination of a low bit rate digital voice message

• US 6,418,407 B1
• Filed: 09/30/1999
• Issued: 07/09/2002
• Est. Priority Date: 09/30/1999
• Status: Expired due to Fees

• Current Assignee: Motorola, Inc. (Motorola Solutions, Inc.)
• Original Assignee: Motorola, Inc. (Motorola Solutions, Inc.)
• Inventors: Huang, Jian-Cheng, Simpson, Floyd, Satyamurti, Sunil, Finlon, Kenneth
• Primary Examiner(s): Banks-Harold, Marsha D.
• Assistant Examiner(s): ABEBE, DANIEL DEMELASH
• Application Number:
  US09/410,007
• Time in Patent Office: 1,013 Days
• Field of Search: 704/207, 704/208, 704/209, 704/217, 704/223, 704/219, 704/220, 704/261
• US Class Current: 704/207
• CPC Class Codes: G10L 19/09 Long term prediction, i.e. removing periodical redundancies, e.g. by using adaptive codebook or pitch predictor
• CPC Class Codes: G10L 19/10 the excitation function being a multipulse excitation
• CPC Class Codes: G10L 25/90 Pitch determination of speech signals

Abstract

A pitch determiner (931) of a system controller (106) that generates a smoothed pitch value for a current frame of a low bit rate voice message includes a pitch function generator (955) that generates a pitch detection function (PDF) for each frame of digital samples of a voice signal, a pitch candidate selector (960) that selects a future frame pitch candidate from a pitch detection function (PDF), and a pitch adjuster (978) that generates the smoothed pitch value. The pitch adjuster includes a subharmonic pitch corrector (965) that determines a future frame pitch value by performing pitch subharmonic correction of a future frame pitch candidate using a roughness factor of the frequency transformed window.

Claims

1. A system controller comprises a pitch determiner that generates a smoothed pitch value for a current frame of a low bit rate voice message, the pitch determiner comprising:

a pitch function generator that generates a pitch detection function (PDF) for each frame of digital samples of a voice signal;

a pitch candidate selector that selects a future frame pitch candidate from a pitch detection function (PDF); and

a subharmonic pitch corrector that determines a future frame pitch value by performing pitch subharmonic correction of the future frame pitch candidate using a roughness factor of the frequency transformed window.

2. The pitch determiner according to claim 1, wherein the pitch function generator comprises a pitch function selector that generates the pitch detection function based on a plurality of band autocorrelations.

3. The pitch determiner according to claim 1, wherein the pitch candidate selector comprises:

a low frequency search function that identifies a smallest low frequency peak of the PDF using a fine tune function, and

a high frequency search function that identifies a largest high frequency peak of the PDF using the fine tune function.

4. A system controller comprises a pitch function generator that generates a smoothed pitch value for a current frame of a low bit rate voice message, the pitch function generator comprising:

a band correlator that determines a plurality of band autocorrelations that correspond to a plurality of bands of a frequency transformed window of the digital samples, the window being related to a future frame of digital samples; and

a pitch function selector that generates the pitch detection function based on the plurality of band autocorrelations, wherein the pitch function selector $\mathrm{generates}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\mathrm{\Gamma <br><br>}}_n=M<br><br>\text{\hspace{1em}<br><br>}<br><br>\max <br><br>\left(0,<br><br>Y_n<br><br>-{\max }_{k=0}^K<br><br><br><br>Y_k<br><br>-P\right)$$\mathrm{for}<br><br>\text{\hspace{1em}<br><br>}<br><br>n<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{from}<br><br>\text{\hspace{1em}<br><br>}<br><br>1<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{to}<br><br>\text{\hspace{1em}<br><br>}<br><br>K<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{when}<br><br>\text{\hspace{1em}<br><br>}<br><br>r_{\max }^{\left[1\right]}$

is less than Q and e_l is greater than R, wherein

Γ

_n is a value of the pitch detection function,

n is an index,

r_max^[1] is a maximum value of r_n^[1] for n from 1 to K,

r_n^[1] is a first band autocorrelation value,

K is a quantity of values in the frequency transformed window,

Y_n is a value in the frequency transformed window,

e_l is a first band entropy value, and

M, P, Q, and R are predetermined positive real values.

5. A system controller comprises a pitch candidate selector that selects a future frame pitch candidate from a pitch detection function (PDF), the pitch candidate selector comprising:

a fine tune function that determines a fine tune peak frequency of a relative peak of the PDF;

a low frequency search function that identifies a smallest low frequency peak of the PDF using the fine tune function;

a high frequency search function that identifies a largest high frequency peak of the PDF using the fine tune function; and

a rough pitch candidate selector that selects one of the smallest low frequency peak and the largest high frequency peak as a future frame rough pitch candidate.

6. The pitch candidate selector according to claim 5, wherein the low frequency search function determines a peak frequency of the smallest low frequency peak of the PDF as the peak frequency of a lowest frequency relative peak that has a magnitude greater than a first predetermined proportion of a greatest peak magnitude of the PDF or that has a magnitude greater than a second predetermined proportion of the greatest peak magnitude of the PDF and for which a multiple of the fine tune peak frequency is within a predetermined frequency range of the frequency of the greatest peak magnitude of the PDF.

7. The pitch candidate selector according to claim 5, wherein the high frequency search function determines a peak frequency of the largest high frequency peak of the PDF as the peak frequency of a highest relative peak that has a magnitude greater than a predetermined proportion of the greatest peak magnitude of the PDF and for which a multiple of the fine tune peak frequency is within a predetermined frequency range of the frequency of the greatest peak magnitude of the PDF.

8. The pitch candidate selector according to claim 5, wherein the rough candidate selector selects the largest high frequency peak as the rough pitch candidate when the smallest low frequency peak and the largest high frequency peak do not match.

9. The pitch candidate selector according to claim 5, wherein the fine tune function performs a polynomial interpolation adjustment to determine the peak frequency of the relative peak.

10. A system controller comprises a pitch adjuster that generates a smoothed pitch value for a current frame of digital samples of a voice signal, the pitch adjuster comprising:

a subharmonic pitch corrector that determines a future frame pitch value by performing pitch subharmonic correction of a future frame pitch candidate using a roughness factor of the frequency transformed window; and

a pitch smoothing function that determines a smoothed pitch value as one of an integer multiple of a current frame pitch value, the current frame pitch value, and an integer sub-multiple of the current frame pitch value.

11. The pitch adjuster according to claim 10, wherein the subharmonic pitch corrector comprises:

a roughness factor function that determines the roughness factor from the magnitudes of all harmonic peaks of a magnitude spectrum and magnitudes of all harmonic peaks of a logarithmic spectrum of the frequency transformed window.

12. The pitch adjuster according to claim 11, wherein the roughness factor function uses a difference between the value of every other harmonic peak in the logarithmic magnitude spectrum and an average of the values of the two peaks adjacent thereto.

13. The pitch adjuster according to claim 10, wherein the roughness factor, β

, is given by $\mathrm{\beta <br><br>}=\frac{\underset{m=1}{\overset{\lfloor <br><br>180/f_0^c<br><br>\left[1\right]\rfloor <br><br>}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br><br><br>Y_{k_{2<br><br>m+1}}<br><br><br><br>\left[0.5<br><br>\left(\log <br><br><br><br>Y_{k_{2<br><br>m+2}}<br><br>+\log <br><br><br><br>Y_{k_{2<br><br>m}}<br><br>\right)-\log <br><br><br><br>Y_{k_{2<br><br>m+1}}<br><br>\right]}{\underset{m=1}{\overset{\lfloor <br><br>180/f_0^c<br><br>\left[1\right]\rfloor <br><br>}{\sum <br><br>}}<br><br><br><br>Y_{k_{2<br><br>m+1}}<br><br>},$

wherein Y is the frequency transformed window and ƒ

₀^c[1] is the future frame pitch candidate.

14. The pitch adjuster according to claim 10, wherein the subharmonic pitch corrector further comprises:

a high roughness decision function that doubles the future frame pitch candidate when the roughness factor β

exceeds a first predetermined value; and

a neural decision function that determines whether to double the future frame pitch candidate using a neural network.

15. The pitch adjuster according to claim 14, wherein the output of the neural network is based on inputs comprising at least one of the roughness factor, a ratio of the mid-term pitch value to the future frame pitch candidate, and a ratio of a maximum magnitude of the pitch detection function within a narrow frequency range around a frequency that is one third the future frame pitch candidate to the magnitude of the pitch detection function at the future frame pitch candidate.

16. A system controller comprises a pitch determiner that generates a smoothed pitch value for a current frame of a low bit rate voice message, the pitch determiner comprising:

a band autocorrelator that determines a plurality of band autocorrelations that correspond to a plurality of bands of a frequency transformed window of the digital samples, the frequency transformed window corresponding to a future frame of digital samples, comprising

a vector filter that generates a reverse filtered spectrum by performing a magnitude transform, a logarithmic transform, and a reverse spectral filtering of the frequency transformed window, and

a spectral autocorrelator that generates the band autocorrelations by applying a spectral autocorrelation function to each band of the reverse filtered spectrum;

a pitch function generator that determines a pitch detection function using the plurality of band autocorrelations;

a pitch candidate selector that selects a future frame pitch candidate from the pitch detection function; and

a pitch adjuster that generates a smoothed pitch value from the future frame pitch candidate and the pitch detection function, comprising

a subharmonic pitch corrector that determines a corrected future frame pitch value by performing pitch subharmonic correction of the future frame pitch candidate using a roughness measure of the frequency transformed window, and

a pitch smoother that determines a smoothed pitch value from the corrected future frame pitch value, the current frame pitch value, and a past frame pitch value.

17. A method used in a system controller that generates a smoothed pitch value for a current frame of a low bit rate voice message, the method comprising the steps of:

generating a pitch detection function (PDF) for each frame of digital samples of a voice signal, comprising the step of

generating the pitch detection function based on a plurality of band autocorrelations;

selecting a future frame pitch candidate from a pitch detection function (PDF), comprising the steps of

identifying a smallest low frequency peak of the PDF using a fine tune function, and

identifying a largest high frequency peak of the PDF using the fine tune function; and

generating the smoothed pitch value, comprising a step of

determining a future frame pitch value by performing pitch subharmonic correction of a future frame pitch candidate using a roughness factor of the frequency transformed window.