Speech detection apparatus not affected by input energy or background noise levels

• US 5,293,588 A
• Filed: 04/09/1991
• Issued: 03/08/1994
• Est. Priority Date: 04/09/1990
• Status: Expired due to Term

• Current Assignee: Kabushiki Kaisha Toshiba (Toshiba Corporation)
• Original Assignee: Kabushiki Kaisha Toshiba (Toshiba Corporation)
• Inventors: Satoh, Hideki, Nitta, Tsuneo
• Primary Examiner(s): Fleming, Michael R.
• Assistant Examiner(s): Doerrler, Michelle
• Application Number:
  US07/682,079
• Time in Patent Office: 1,064 Days
• Field of Search: 381/29-47, 395/2.42
• US Class Current: 704/233
• CPC Class Codes: G10L 25/78 Detection of presence or absence of voice signals switching of direction of transmission by voice frequency in two-way loud-speaking telephone systems H04M9/10

Abstract

A speech detection apparatus capable of reliably detecting speech segments in audio signals regardless of the levels of input audio signals and background noises. In the apparatus, a parameter of input audio signals is calculated frame by frame, and then compared with a threshold in order to judge each input frame as one of a speech segment and a noise segment, while the parameters of the input frames judged as the noise segments are stored in the buffer and the threshold is updated according to the parameters stored in the buffer. The apparatus may utilize a transformed parameter obtained from the parameter, in which the difference between speech and noise is emphasized, and noise standard patterns are constructed from the parameters of the input frames pre-estimated as noise segments.

Claims

1. A speech detection apparatus, comprising:

means for calculating a parameter for each one of input frames of an input speech;

means for judging said each one of the input frames as a speech segment or a noise segment;

buffer means for storing the parameters of the input frame which are judged noise segments by the judging means; and

means for transforming the parameter calculated by the calculating means into a transformed parameter in which a difference between speech and noise is emphasized by using the parameters stored in the buffer means, and supplying the transformed parameter to the judging means such that the judging means judges by searching a predetermined standard pattern of a class to which the transformed parameter belongs among a plurality of standard patterns for the speech segment and the noise segment.

2. The speech detection apparatus of claim 1, wherein the transforming means transforms the parameter into the transformed parameter which is a difference between a the parameter and a mean vector of a set of the parameters stored in the buffer means.

3. The speech detection apparatus of claim 1, wherein the transforming means transforms the parameter into the transformed parameter which is a normalized difference between the parameter and a mean vector of a set of the parameters stored in the buffer means, where the transformed parameter is normalized by a standard deviation of elements of a set of the parameters stored in the buffer means.

4. The speech detection apparatus of claim 1, wherein the judging means judges said each one of the input frames as a speech segment or a noise segment by searching a predetermined standard pattern which has a minimum distance from the transformed parameter of said each one of the input frames.

5. The speech detection apparatus of claim 4, wherein the distance between the transformed parameter of said each one of the input frames and the standard pattern of a class ω

_i is defined as;

space="preserve" listing-type="equation">D.sub.i (Y)=(Y-μ

.sub.i).sup.t Σ

.sub.i.sup.-1 (Y-μ

.sub.i)+1n|Σ

.sub.i |

where D_i (Y) is the distance, Y is the transformed parameter, μ

_i is a mean vector of a set of the transformed parameters of the class ω

_i, Σ

_i is a covariance matrix of the set of the transformed parameters of a class ω

_i, i is an integer, and (Y-μ

_i)^t denotes a transpose of (Y-μ

_i).

6. The speech detection apparatus of claim 5, wherein a trial set of a class ω

_i contains L transformed parameters defined by;

space="preserve" listing-type="equation">Y.sub.i (j)=(y.sub.i1 (j),y.sub.i2 (j), . . . ,y.sub.im (j), . . . ,y.sub.ir (j))

where j represents the j-th element of the trial set and 1≦

j≦

L, the mean vector μ

_i is defined as an r-dimensional vector given by;

##EQU9## and the covariance matrix Σ

_i is defined as an r×

r matrix given by;

##EQU10## and the standard pattern is given by a pair (μ

_i, Σ

_i) formed by the mean vector μ

_i and the covariance matrix Σ

_i, where m and n are integers.

7. A speech detection apparatus, comprising:

means for calculating a parameter of each one of input frames of an input speech;

means for comparing the parameter calculated by the calculating means with a threshold in order to pre-estimate noise segments in input audio signals;

buffer means for storing the parameters of the input frames which are pre-estimated as the noise segments by the comparing means;

means for updating the threshold according to the parameters stored in the buffer means;

means for judging said each one of the input frames as a speech segment or a noise segment; and

means for transforming the parameter calculated by the calculating means into a transformed parameter in which a difference between speech and noise is emphasized by using the parameters stored in the buffer means, and supplying the transformed parameter to the judging means such that the judging means judges by searching a predetermined standard pattern of a class to which the transformed parameter belongs among a plurality of standard patterns for the speech segment and the noise segment.

8. A speech detection apparatus, comprising:

means for calculating a parameter of each one of input frames of an input speech;

means for pre-estimating noise segments in input audio signals of the input speech;

means for constructing a plurality of noise standard patterns from the parameters of the noise segments pre-estimated by the pre-estimating means; and

means for judging said each one of the input frames as a speech segment or a noise segment by comparing the parameter of the input frame with said plurality of the noise standard patterns constructed by the constructing means and a plurality of predetermined speech standard patterns.

9. The speech detection apparatus of claim 8, wherein the pre-estimating means includes:

means for obtaining the energy of said each one of the input frames;

means for comparing the energy obtained by the obtaining means with a threshold in order to estimate said each one of the input frames as a speech segment or a noise segment; and

means for updating the threshold according to the energy obtained by the obtaining means.

10. The speech detection apparatus of claim 9, wherein the updating means updates the threshold such that when the energy P(n) of an n-th input frame and a current threshold value T(n) for the threshold satisfy the relation:

space="preserve" listing-type="equation">P(n)<

T(n)-P(n)×

(α

-1)

where α

is a constant and n is an integer, then the threshold value T(n) is updated to a new threshold value T(n+1) given by;

space="preserve" listing-type="equation">T(n+1)=P(n)×

α

whereas when the energy P(n) and the current threshold value T(n) satisfy the relation;

space="preserve" listing-type="equation">P(n)≧

T(n)-P(n)×

(α

-1)

then the threshold value T(n) is updated to a new threshold value T(n+1) given by;

space="preserve" listing-type="equation">T(n+1)=P(n)×

γ

where γ

is a constant.

11. The speech detection apparatus of claim 8, wherein the constructing means constructs the noise standard patterns by calculating a mean vector and a covariance matrix for a set of the parameters of the input frames which are pre-estimated as the noise segments by the pre-estimating means.

12. The speech detection apparatus of claim 8, wherein the judging means judges said each one of the input frames by searching one of the standard patterns which has a minimum distance from the parameter of said each one of the input frames.

13. The speech detection apparatus of claim 12, wherein the distance between the parameter of said each one of the input frames and the standard patterns of a class ω

_i is defined as;

##EQU11## where D_i (X) is the distance, X is the parameter of the input frame, μ

_i is a mean vector of a set of the parameters of the class ω

_i, Σ

_i is a covariance matrix of the set of the parameters of the class ω

_i, i is an integer, and (X-μ

_i)^t denotes a transpose of (X-μ

_i).

14. The speech detection apparatus of claim 13, wherein a trial set of a class ω

_i contains L transformed parameters defined by;

space="preserve" listing-type="equation">X.sub.i (j)=(x.sub.i1 (j),x.sub.i2 (j), . . . ,x.sub.im (j), . . . ,x.sub.ip (j))

where j represents the j-th element of the trial set and 1≦

j≦

L, the mean vector μ

_i is defined as an p-dimensional vector given by;

##EQU12## and the covariance matrix Σ

_i is defined as a p×

p matrix given by;

##EQU13## and the standard pattern is given by a pair (μ

_i, Σ

_i) formed by the mean vector μ

_i and the covariance matrix Σ

_i, where m and n are integers.

15. A speech detection apparatus, comprising:

means for calculating a parameter of each one of input frames of an input speech;

means for transforming the parameter calculated by the calculating means into a transformed parameter in which a difference between speech and noise is emphasized;

means for constructing a plurality of noise standard patterns from the transformed parameters; and

means for judging said each one of the input frames as a speech segment or a noise segment by comparing the transformed parameter obtained by the transforming means with said plurality of noise standard patterns constructed by the constructing means.

16. The speech detection apparatus of claim 15, wherein the transforming means includes:

means for comparing the parameter calculated by the calculating means with a threshold in order to estimate said each one of the input frames as a speech segment or a noise segment, and to control the constructing means such that the constructing means constructs the noise standard patterns from the transformed parameters of the input frames estimated as the noise segments;

buffer means for storing the parameters of the input frames which are estimated as the noise segments by the comparing means;

means for updating the threshold according to the parameters stored in the buffer means; and

transformation means for obtaining the transformed parameter from the parameter by using the parameters stored in the buffer means.