Detection of periodicity information from an audio signal

• US 5,970,441 A
• Filed: 08/25/1997
• Issued: 10/19/1999
• Est. Priority Date: 08/25/1997
• Status: Expired due to Term

• Current Assignee: Telefonaktiebolaget LM Ericsson
• Original Assignee: Telefonaktiebolaget LM Ericsson
• Inventors: Mekuria, Fisseha
• Primary Examiner(s): Dorvil, Richemond
• Application Number:
  US08/917,224
• Time in Patent Office: 785 Days
• Field of Search: 704/207, 704/208, 704/205, 704/214, 704/206, 704/209, 704/210, 704/215, 704/228, 704/227, 704/226, 704/229, 704/225, 704/233, 704/219
• US Class Current: 704/207
• CPC Class Codes: G10L 2025/786 Adaptive threshold
• CPC Class Codes: G10L 25/90 Pitch determination of speech signals

Abstract

A waveform-based technique for generating periodicity information from an input signal includes generating a pre-processed signal by applying low pass and non-linear filtering to the input signal, wherein the pre-processed signal has highlighted speech pitch tracks. An adaptive threshold algorithm is applied to the pre-processed signal to generate a detection signal having waveform segments whose peaks are separated by a pitch period of the input signal. A period between peaks in the detection signal is determined that indicates the periodicity information. Information about the period between the peaks in the detection signal is then used to adapt a scaling value to be used by the adaptive threshold algorithm in a subsequent step. The periodicity information may be utilized in a voice activity detector in a telephonic communications system.

Claims

1. A method of generating periodicity information from an input audio signal, comprising the steps of:

generating a pre-processed signal by applying low pass and non-linear filtering to remove information from the input audio signal, wherein the removed information is not indicative of speech pitch information;

transforming the pre-processed signal in accordance with an adaptive threshold algorithm to generate a detection signal having waveform segments whose peaks are separated by a pitch period of the input audio signal;

determining a period between peaks in the detection signal to generate the periodicity information; and

using information about the period between the peaks in the detection signal to adapt a scaling value that is used by the adaptive threshold algorithm when processing a subsequent pre-processed signal.

2. The method of claim 1, wherein the non-linear filtering is performed in accordance with the following equation:

##EQU6## wherein y(k) is a kth sample of the low pass filtered input audio signal, β

is a value for adjusting magnitude of the pre-processed signal, x(k) is a kth input audio signal, and n is a value for adjusting peaks in the pre-processed signal.

3. The method of claim 2, wherein values for n and β

are selected as a function of a signal to noise ratio of the input audio signal.

4. The method of claim 3, wherein the adaptive threshold algorithm generates a threshold signal V_th (i) in accordance with the following equation:

##EQU7## where y(k) is a kth sample of the pre-processed signal, G(i) is a scaling factor at time i, and N(i) is a number of samples between peaks in a signal that was generated by a previously performed adaptive threshold computation step.

5. The method of claim 4, further comprising the step of adjusting the scaling factor, G(i), as a function of the value N(i).

6. The method of claim 5, wherein the step of adjusting the scaling factor, G(i), comprises the steps of:

comparing N(i) to a predetermined value;

increasing G(i) if N(i) is less than the predetermined value; and

decreasing G(i) if N(i) is greater than the predetermined value.

7. The method of claim 2, wherein the adaptive threshold algorithm generates a threshold signal V_th (i) in accordance with the following equation:

##EQU8## where y(k) is a kth sample of the pre-processed signal, G(i) is a scaling factor at time i, and N(i) is a number of samples between peaks in a signal that was generated by a previously performed adaptive threshold computation step.

8. The method of claim 7, further comprising the step of adjusting the scaling factor, G(i), as a function of the value N(i).

9. The method of claim 8, wherein the step of adjusting the scaling factor, G(i), comprises the steps of:

comparing N(i) to a predetermined value;

increasing G(i) if N(i) is less than the predetermined value; and

decreasing G(i) if N(i) is greater than the predetermined value.

10. The method of claim 1, wherein the adaptive threshold algorithm generates a threshold signal V_th (i) in accordance with the following equation:

##EQU9## where y(k) is a kth sample of the pre-processed signal, G(i) is a scaling factor at time i, and N(i) is a number of samples between peaks in a signal that was generated by a previously performed adaptive threshold computation step.

11. The method of claim 10, further comprising the step of adjusting the scaling factor, G(i), as a function of the value N(i).

12. The method of claim 11, wherein the step of adjusting the scaling factor, G(i), comprises the steps of:

comparing N(i) to a predetermined value;

increasing G(i) if N(i) is less than the predetermined value; and

decreasing G(i) if N(i) is greater than the predetermined value.

13. The method of claim 1, wherein the input audio signal is an input speech signal.

14. An apparatus for generating periodicity information from an input audio signal, comprising:

means for generating a pre-processed signal by applying low pass and non-linear filtering to remove information from the input audio signal, wherein the removed information is not indicative of speech pitch information;

means for transforming the pre-processed signal in accordance with an adaptive threshold algorithm to generate a detection signal having waveform segments whose peaks are separated by a pitch period of the input audio signal;

means for determining a period between peaks in the detection signal to generate the periodicity information; and

means for using information about the period between the peaks in the detection signal to adapt a scaling value that is used by the adaptive threshold algorithm when processing a subsequent pre-processed signal.

15. The apparatus of claim 14, wherein the non-linear filtering is performed in accordance with the following equation:

##EQU10## wherein y(k) is a kth sample of the low pass filtered input audio signal, β

is a value for adjusting magnitude of the pre-processes signal, x(k) is a kth input audio signal, and n is a value for adjusting peaks of the pre-processed signal.

16. The apparatus of claim 15, wherein values for n and β

are selected as a function of a signal to noise ratio of the input audio signal.

17. The apparatus of claim 16, wherein the adaptive threshold algorithm generates a threshold signal V_th (i) in accordance with the following equation:

##EQU11## where y(k) is a kth sample of the pre-processed signal, G(i) is a scaling factor at time i, and N(i) is a number of samples between peaks in a previously generated detection signal.

18. The apparatus of claim 17, further comprising means for adjusting the scaling factor, G(i), as a function of the value N(i).

19. The apparatus of claim 18, wherein the means for adjusting the scaling factor, G(i), comprises:

means for comparing N(i) to a predetermined value;

means for increasing G(i) if N(i) is less than the predetermined value; and

means for decreasing G(i) if N(i) is greater than the predetermined value.

20. The apparatus of claim 15, wherein the adaptive threshold algorithm generates a threshold signal V_th (i) in accordance with the following equation:

##EQU12## where y(k) is a kth sample of the pre-processed signal, G(i) is a scaling factor at time i, and N(i) is a number of samples between peaks in a previously generated detection signal.

21. The apparatus of claim 20, further comprising means for adjusting the scaling factor, G(i), as a function of the value N(i).

22. The apparatus of claim 21, wherein the means for adjusting the scaling factor, G(i), comprises:

means for comparing N(i) to a predetermined value;

means for increasing G(i) if N(i) is less than the predetermined value; and

means for decreasing G(i) if N(i) is greater than the predetermined value.

23. The apparatus of claim 14, wherein the means for transforming the pre-processed signal in accordance with the adaptive threshold algorithm generates a threshold signal V_th (i) in accordance with the following equation:

##EQU13## where y(k) is a kth sample of the pre-processed signal, G(i) is a scaling factor at time i, and N(i) is a number of samples between peaks in a previously generated detection signal.

24. The apparatus of claim 23, further comprising means for adjusting the scaling factor, G(i), as a function of the value N(i).

25. The apparatus of claim 24, wherein the means for adjusting the scaling factor, G(i), comprises:

means for comparing N(i) to a predetermined value;

means for increasing G(i) if N(i) is less than the predetermined value; and

means for decreasing G(i) if N(i) is greater than the predetermined value.

26. The apparatus of claim 14, wherein the input audio signal is an input speech signal.