Linear predictive residual representation via non-iterative spectral reconstruction

• US 5,067,158 A
• Filed: 06/11/1985
• Issued: 11/19/1991
• Est. Priority Date: 06/11/1985
• Status: Expired due to Fees

• Current Assignee: Texas Instruments, Inc.
• Original Assignee: Texas Instruments, Inc.
• Inventors: Arjmand, Masud M.
• Primary Examiner(s): Shaw, Dale M.
• Assistant Examiner(s): Knepper, David D.
• Application Number:
  US06/744,171
• Time in Patent Office: 2,352 Days
• Field of Search: 381/29-50, 364/513.5
• US Class Current: 704/219
• CPC Class Codes: G10L 19/08 Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters
• CPC Class Codes: G10L 25/27 characterised by the analysis technique

Abstract

Method of encoding speech at medium to high bit rates while maintaining very high speech quality, as specifically directed to the coding of the linear predictive (LPC) residual signal using either its Fourier Transform magnitude or phase. In particular, the LPC residual of the speech signal is coded using minimum phase spectral reconstruction techniques by transforming the LPC residual signal in a manner approximately a minimum phase signal, and then applying spectral reconstruction techniques for representing the LPC residual signal by either its Fourier Transform magnitude or phase. The non-iterative spectral reconstruction technique is based upon cepstral coefficients through which the magnitude and phase of a minimum phase signal are related. The LPC residual as reconstructed and regenerated is used as an excitation signal to a LPC synthesis filter in the generation of analog speech signals via speech synthesis from which audible speech may be produced.

Claims

1. A method of encoding a linear predictive residual signal as derived from an analog speech signal, wherein said linear predictive residual signal is in the form of a plurality of frames of digital speech data, said method comprising the steps of:

transforming each frame of digital speech data to a frame of digital speech data at least approximating minimum phase; and

subjecting the transformed frame of digital speech data at least approximating minimum phase to a Fourier Transform procedure, thereby providing an encoded version of the frame in which one of the magnitude and the phase information is representative of the original frame of digital speech data which forms part of the original linear predictive residual signal, and the other of the magnitude and the phase information does not occur in the encoded version of the frame.

2. A method as set forth in claim 1, wherein the Fourier Transform magnitude is the encoded version of the original frame of digital speech data which forms part of the original linear predictive residual signal.

3. A method as set forth in claim 1, wherein the Fourier Transform phase is the encoded version of the original frame of digital speech data which forms part of the original linear predictive residual signal.

4. A method as set forth in claim 1, further including restoring said encoded version of the frame to the original frame of digital speech data;

and

regenerating the linear predictive residual signal.

5. A method as set forth in claim 4, further including employing the regenerated linear predictive residual signal as an excitation signal in conjunction with linear predictive speech parameters in a linear predictive speech synthesis filter from which audible speech may be derived.

6. A method of encoding a linear predictive residual signal as derived from an analog speech signal, wherein said linear predictive residual signal is in the form of a plurality of frames of digital speech data, said method comprising the steps of:

searching each frame of digital speech data to detect the peak residual value occurring therein;

time-shifting the digital speech data included in the frame to align the peak residual value with the origin of the frame;

determining a dispersion measure D for the frame in accordance with the relationship ##EQU7## where n is the number of samples included in the frame of digital speech data, and x is the energy value of a respective sample of the frame;

weighting the frame of digital speech data in a manner inversely proportional to the dispersion measure D to provide a transformed frame of digital speech data at least approximating a minimum phase signal; and

subjecting the weighted frame of digital speech data to a Fourier Transform procedure, thereby providing an encoded version of the frame in which one of the magnitude and the phase information is representative of the original frame of digital speech data which forms part of the original linear predictive residual signal.

7. A method as set forth in claim 6, wherein weighting the frame of digital speech data is accomplished by applying a weighting factor a in accordance with the relationship

8. A method as set forth in claim 7, wherein the magnitude information is the encoded version of the frame representative of the original frame of digital speech data.

9. A method as set forth in claim 7, wherein the phase information is the encoded version representative of the original frame of digital speech data.

10. A method as set forth in claim 7, further including restoring the encoded version of the frame to the transformed frame of digital speech data at least approximating minimum phase by employing a non-iterative spectral reconstruction, and

removing the weighting of the frame of digital speech data and time-shifting the digital speech data included in the frame to return the peak residual value occurring therein to its original position, thereby regenerating the original frame of digital speech data which forms part of the original linear predictive residual signal.

11. A method as set forth in claim 10, further including employing the regenerated linear predictive residual signal as an excitation signal with linear predictive speech parameters in a linear predictive coding speech synthesis filter from which audible speech is to be derived.