US5692104A
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US
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Method and apparatus for detecting end points of speech activity
Assignee: Apple Inc
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Filing: 1994-09-27
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Granted: 1997-11-25
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Expires: 2014-09-27
Abstract
Abstract A method and apparatus for detecting end points of speech activity in an input signal using spectral representation vectors performs beginning point detection using spectral representation vectors for the spectrum of each sample of the input signal and a spectral representation vector for the steady state portion of the input signal. The beginning point of speech is detected when the spectrum diverges from the steady state portion of the input signal. Once the beginning point has been detected, the spectral representation vectors of the input signal are used to determine the ending point of the sound in the signal. The ending point of speech is detected when the spectrum converges towards the steady state portion of the input signal. After both the beginning and ending of the sound are detected, vector quantization distortion can be used to classify the sound as speech or noise.
Inventors
- 👤 Yen-Lu Chow
- 👤 Erik P. Staats
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-10-23 22:59
CPC Classifications
G; G10; G10L; G10L25/00; G10L25/78; G10L25/87; G10L25/03; G10L25/09; G10L25/24
Claims Analysis
Total Claims: 36
Claim 1
Independent Claim
169 words
A method of detecting speech activity in a data input stream comprising the steps of: (a) generating a set of spectral representation vectors to represent the data input stream, wherein each spectral representation vector of the set of spectral representation vectors represents a predetermined portion of the data input stream; (b) generating a steady state spectral representation vector indicative of the state of the data input stream at a first predetermined portion of the data input stream; (c) comparing a spectral representation vector corresponding to the first predetermined portion of the data input stream to the steady state spectral representation vector; (d) determining a first end point of speech activity when the set of spectral representation vectors diverges from the steady state spectral representation vector; and (e) determining a second end point of speech activity when a predetermined number of spectral representation vectors of the set of spectral representation vectors are within a predetermined distance of the steady state spectral representation vector for a continuous predetermined period of time.
Claim 2
Independent Claim
169 words
A method of detecting speech activity in a data input stream comprising the steps of: (a) generating a set of spectral representation vectors to represent the data input stream, wherein each spectral representation vector of the set of spectral representation vectors represents a predetermined portion of the data input stream; (b) generating a steady state spectral representation vector indicative of the state of the data input stream at a first predetermined portion of the data input stream; (c) comparing a spectral representation vector corresponding to the first predetermined portion of the data input stream to the steady state spectral representation vector; (d) determining a first end point of speech activity when the set of spectral representation vectors diverges from the steady state spectral representation vector; and (e) determining a second end point of speech activity when a predetermined number of spectral representation vectors of the set of spectral representation vectors are within a predetermined distance of the steady state spectral representation vector for a continuous predetermined period of time.
Claim 3
Independent Claim
118 words
A method of detecting speech activity in a data input stream comprising the steps of: (a) generating a set of autocorrelation vectors to represent the data input stream, wherein each autocorrelation vector of the set of autocorrelation vectors represents a predetermined portion of the data input stream; (b) generating a steady state autocorrelation vector indicative of the state of the data input stream at a first predetermined portion of the data input stream; (c) comparing an autocorrelation vector corresponding to the first predetermined portion of the data input stream to the steady state autocorrelation vector; and (d) determining a first end point of speech activity when the set of autocorrelation vectors diverges from the steady state autocorrelation vector.
Claim 4
Independent Claim
118 words
A method of detecting speech activity in a data input stream comprising the steps of: (a) generating a set of autocorrelation vectors to represent the data input stream, wherein each autocorrelation vector of the set of autocorrelation vectors represents a predetermined portion of the data input stream; (b) generating a steady state autocorrelation vector indicative of the state of the data input stream at a first predetermined portion of the data input stream; (c) comparing an autocorrelation vector corresponding to the first predetermined portion of the data input stream to the steady state autocorrelation vector; and (d) determining a first end point of speech activity when the set of autocorrelation vectors diverges from the steady state autocorrelation vector.
Claim 5
Dependent Claim
31 words
The method of claim 2, further comprising the step of: (e) determining a second point of speech activity when the set of autocorrelation vectors converges towards the steady state autocorrelation vector.
Claim 6
Dependent Claim
49 words
The method of claim 3, wherein the step (e) comprises determining the second end point of speech activity when a predetermined number of autocorrelation vectors of the set of autocorrelation vectors are within a predetermined distance of the steady state autocorrelation vector for a continuous predetermined period of time.
Claim 7
Dependent Claim
121 words
The method of claim 3, further comprising the steps of: (f) calculating a first distortion for each of a plurality of autocorrelation vectors of the set of autocorrelation vectors between each of the plurality of autocorrelation vectors and a speech codebook; (g) calculating a second distortion for each of a plurality of autocorrelation vectors of the set of autocorrelation vectors between each of the plurality of autocorrelation vectors and the noise codebook; and (h) classifying the speech activity as speech, provided the first distortion is greater than a speech threshold for a first predetermined period of time, otherwise classifying the speech activity as noise, provided the second distortion is greater than a noise threshold for the first predetermined period of time.
Claim 8
Dependent Claim
49 words
The method of claim 2, wherein the step (d) comprises determining the first end point of speech activity when a predetermined number of autocorrelation vectors of the set of autocorrelation vectors are a predetermined distance away from the steady state autocorrelation vector for a continuous predetermined period of time.
Claim 9
Independent Claim
126 words
A method of detecting speech activity in a data input stream comprising the steps of: (a) generating a set of Fourier Transform vectors to represent the data input stream, wherein each Fourier Transform vector of the set of Fourier Transform vectors represents a predetermined portion of the data input stream; (b) generating a steady state Fourier Transform vector indicative of the state of the data input stream at a first predetermined portion of the data input stream; (c) comparing a Fourier Transform vector corresponding to the first predetermined portion of the data input stream to the steady state Fourier Transform vector; and (d) determining a first end point of speech activity when the set of Fourier Transform vectors diverges from the steady state Fourier Transform vector.
Claim 10
Independent Claim
126 words
A method of detecting speech activity in a data input stream comprising the steps of: (a) generating a set of Fourier Transform vectors to represent the data input stream, wherein each Fourier Transform vector of the set of Fourier Transform vectors represents a predetermined portion of the data input stream; (b) generating a steady state Fourier Transform vector indicative of the state of the data input stream at a first predetermined portion of the data input stream; (c) comparing a Fourier Transform vector corresponding to the first predetermined portion of the data input stream to the steady state Fourier Transform vector; and (d) determining a first end point of speech activity when the set of Fourier Transform vectors diverges from the steady state Fourier Transform vector.
Claim 11
Dependent Claim
34 words
The method of claim 7, further comprising the step of: (e) determining a second end point of speech activity when the set of Fourier Transform vectors converges towards the steady state Fourier Transform vector.
Claim 12
Dependent Claim
52 words
The method of claim 8, wherein the step (e) comprises determining the second end point of speech activity when a predetermined number of Fourier Transform vectors of the set of Fourier Transform vectors are within a predetermined distance of the steady state Fourier Transform vector for a continuous predetermined period of time.
Claim 13
Dependent Claim
127 words
The method of claim 8, further comprising the steps of: (f) calculating a first distortion for each of a plurality of Fourier Transform vectors of the set of Fourier Transform vectors between each of the plurality of Fourier Transform vectors and a speech codebook; (g) calculating a second distortion for each of a plurality of Fourier Transform vectors of the set of Fourier Transform vectors between each of the plurality of Fourier Transform vectors and the noise codebook; and (h) classifying the speech activity as speech, provided the first distortion is greater than a speech threshold for a first predetermined period of time, otherwise classifying the speech activity as noise, provided the second distortion is greater than a noise threshold for the first predetermined period of time.
Claim 14
Dependent Claim
52 words
The method of claim 7, wherein the step (d) comprises determining the first end point of speech activity when a predetermined number of Fourier Transform vectors of the set of Fourier Transform vectors are a predetermined distance away from the steady state Fourier Transform vector for a continuous predetermined period of time.
Claim 15
Independent Claim
205 words
An apparatus for detecting speech activity in a data input stream comprising: a memory unit; an input device for receiving the data input stream; and a processor coupled to the memory unit and the input device, wherein the processor generates a set of spectral representation vectors to represent the data input stream and stores the set of spectral representation vectors in the memory unit, wherein each spectral representation vector of the set of spectral representation vectors represents a predetermined portion of the data input stream, wherein the processor also generates a steady state spectral representation vector indicative of the state of the data input stream at a first predetermined portion of the data input stream and compares a spectral representation vector corresponding to the first predetermined portion of the data input stream to the steady state spectral representation vector, determines a first end point of speech activity when the set of spectral representation vectors diverges from the steady state spectral representation vector, and determines a second end point of speech activity when a predetermined number of spectral representation vectors of the set of spectral representation vectors are within a predetermined distance of the steady state spectral representation vector for a continuous predetermined period of time.
Claim 16
Independent Claim
205 words
An apparatus for detecting speech activity in a data input stream comprising: a memory unit; an input device for receiving the data input stream; and a processor coupled to the memory unit and the input device, wherein the processor generates a set of spectral representation vectors to represent the data input stream and stores the set of spectral representation vectors in the memory unit, wherein each spectral representation vector of the set of spectral representation vectors represents a predetermined portion of the data input stream, wherein the processor also generates a steady state spectral representation vector indicative of the state of the data input stream at a first predetermined portion of the data input stream and compares a spectral representation vector corresponding to the first predetermined portion of the data input stream to the steady state spectral representation vector, determines a first end point of speech activity when the set of spectral representation vectors diverges from the steady state spectral representation vector, and determines a second end point of speech activity when a predetermined number of spectral representation vectors of the set of spectral representation vectors are within a predetermined distance of the steady state spectral representation vector for a continuous predetermined period of time.
Claim 17
Independent Claim
153 words
An apparatus for detecting speech activity in a data input stream comprising: a memory unit; an input device for receiving the data input stream; a processor coupled to the memory unit and the input device, wherein the processor generates a set of autocorrelation vectors to represent the data input stream and stores the set of autocorrelation vectors in the memory unit, wherein each autocorrelation vector of the set of autocorrelation vectors represents a predetermined portion of the data input stream, wherein the processor also generates a steady state autocorrelation vector indicative of the state of the data input stream at a first predetermined portion of the data input stream and compares an autocorrelation vector corresponding to the first predetermined portion of the data input stream to the steady state autocorrelation vector, and determines a first end point of speech activity when the set of autocorrelation vectors diverges from the steady state autocorrelation vector.
Claim 18
Independent Claim
153 words
An apparatus for detecting speech activity in a data input stream comprising: a memory unit; an input device for receiving the data input stream; a processor coupled to the memory unit and the input device, wherein the processor generates a set of autocorrelation vectors to represent the data input stream and stores the set of autocorrelation vectors in the memory unit, wherein each autocorrelation vector of the set of autocorrelation vectors represents a predetermined portion of the data input stream, wherein the processor also generates a steady state autocorrelation vector indicative of the state of the data input stream at a first predetermined portion of the data input stream and compares an autocorrelation vector corresponding to the first predetermined portion of the data input stream to the steady state autocorrelation vector, and determines a first end point of speech activity when the set of autocorrelation vectors diverges from the steady state autocorrelation vector.
Claim 19
Dependent Claim
29 words
The apparatus of claim 13, wherein the processor determines a second end point of speech activity when the set of autocorrelation vectors converges towards the steady state autocorrelation vector.
Claim 20
Dependent Claim
117 words
The apparatus of claim 14, wherein the processor also calculates a first distortion for each of a plurality of autocorrelation vectors of the set of spectral representation vectors between each of the plurality of autocorrelation vectors and a speech codebook, calculates a second distortion for each of a plurality of autocorrelation vectors of the set of autocorrelation vectors between each of the plurality of autocorrelation vectors and the noise codebook, classifies the speech activity as speech, provided the first distortion is greater than a speech threshold for a first predetermined period of time, and classifies the speech activity as noise, provided the second distortion is greater than a noise threshold for the first predetermined period of time.
Claim 21
Dependent Claim
47 words
The apparatus of claim 13, wherein the processor determines the first end point of speech activity when a predetermined number of autocorrelation vectors of the set of autocorrelation vectors are a predetermined distance away from the steady state autocorrelation vector for a continuous predetermined period of time.
Claim 22
Independent Claim
162 words
An apparatus for detecting speech activity in a data input stream comprising: a memory unit; an input device for receiving the data input stream; a processor coupled to the memory unit and the input device, wherein the processor generates a set of Fourier Transform vectors to represent the data input stream and stores the set of Fourier Transform vectors in the memory unit, wherein each Fourier Transform vector of the set of Fourier Transform vectors represents a predetermined portion of the data input stream, wherein the processor also generates a steady state Fourier Transform vector indicative of the state of the data input stream at a first predetermined portion of the data input stream and compares a Fourier Transform vector corresponding to the first predetermined portion of the data input stream to the steady state Fourier Transform vector, and determines a first end point of speech activity when the set of Fourier Transform vectors diverges from the steady state Fourier Transform vector.
Claim 23
Independent Claim
162 words
An apparatus for detecting speech activity in a data input stream comprising: a memory unit; an input device for receiving the data input stream; a processor coupled to the memory unit and the input device, wherein the processor generates a set of Fourier Transform vectors to represent the data input stream and stores the set of Fourier Transform vectors in the memory unit, wherein each Fourier Transform vector of the set of Fourier Transform vectors represents a predetermined portion of the data input stream, wherein the processor also generates a steady state Fourier Transform vector indicative of the state of the data input stream at a first predetermined portion of the data input stream and compares a Fourier Transform vector corresponding to the first predetermined portion of the data input stream to the steady state Fourier Transform vector, and determines a first end point of speech activity when the set of Fourier Transform vectors diverges from the steady state Fourier Transform vector.
Claim 24
Dependent Claim
31 words
The apparatus of claim 17, wherein the processor determines a second end point of speech activity when the set of Fourier Transform vectors converges towards the steady state Fourier Transform vector.
Claim 25
Dependent Claim
122 words
The apparatus of claim 18, wherein the processor also calculates a first distortion for each of a plurality of Fourier Transform vectors of the set of Fourier Transform vectors between each of the plurality of Fourier Transform vectors and a speech codebook, calculates a second distortion for each of a plurality of Fourier Transform vectors of the set of Fourier Transform vectors between each of the plurality of Fourier Transform vectors and the noise codebook, classifies the speech activity as speech, provided the first distortion is greater than a speech threshold for a first predetermined period of time, and classifies the speech activity as noise, provided the second distortion is greater than a noise threshold for the first predetermined period of time.
Claim 26
Dependent Claim
51 words
The apparatus of claim 17, wherein the processor determines the first end point of speech activity exists when a predetermined number of Fourier Transform vectors of the set of Fourier Transform vectors are a predetermined distance away from the steady state Fourier Transform vector for a continuous predetermined period of time.
Claim 27
Independent Claim
119 words
A method of detecting speech activity in a data input stream comprising the steps of: (a) generating a set of spectral representation vectors to represent a plurality of portions of the data input stream; (b) generating a steady state spectral representation vector indicative of the state of the data input stream at a first portion of the data input stream, wherein the first portion is one of the plurality of portions; (c) comparing a first spectral representation vector representing the first portion of the data input stream to the steady state spectral representation vector; and (d) determining a first end point of speech activity when the set of spectral representation vectors diverges from the steady state spectral representation vector.
Claim 28
Independent Claim
119 words
A method of detecting speech activity in a data input stream comprising the steps of: (a) generating a set of spectral representation vectors to represent a plurality of portions of the data input stream; (b) generating a steady state spectral representation vector indicative of the state of the data input stream at a first portion of the data input stream, wherein the first portion is one of the plurality of portions; (c) comparing a first spectral representation vector representing the first portion of the data input stream to the steady state spectral representation vector; and (d) determining a first end point of speech activity when the set of spectral representation vectors diverges from the steady state spectral representation vector.
Claim 29
Dependent Claim
34 words
The method of claim 21, further comprising the step of: (e) determining a second end point of speech activity when the set of spectral representation vectors converges towards the steady state spectral representation vector.
Claim 30
Dependent Claim
26 words
The method of claim 22, further comprising the step of: (f) determining whether the speech activity more closely resembles a speech codebook or a noise codebook.
Claim 31
Dependent Claim
13 words
The method of claim 21, wherein the spectral representation vectors are autocorrelation vectors.
Claim 32
Independent Claim
159 words
An apparatus for detecting speech activity in a data input stream comprising: a memory unit an input device for receiving the data input stream; and a processor coupled to the memory unit and the input device, wherein the processor generates a set of spectral representation vectors to represent a plurality of portions of the data input stream and stores the set of spectral representation vectors in the memory unit, wherein the processor also generates a steady state spectral representation vector indicative of the state of the data input stream at a first portion of the data input stream, wherein the first portion is one of the plurality of portions, wherein the processor also compares a first spectral representation vector representing the first portion of the data input stream to the steady state spectral representation vector and determines a first end point of speech activity when the set of spectral representation vectors diverges from the steady state spectral representation vector.
Claim 33
Independent Claim
159 words
An apparatus for detecting speech activity in a data input stream comprising: a memory unit an input device for receiving the data input stream; and a processor coupled to the memory unit and the input device, wherein the processor generates a set of spectral representation vectors to represent a plurality of portions of the data input stream and stores the set of spectral representation vectors in the memory unit, wherein the processor also generates a steady state spectral representation vector indicative of the state of the data input stream at a first portion of the data input stream, wherein the first portion is one of the plurality of portions, wherein the processor also compares a first spectral representation vector representing the first portion of the data input stream to the steady state spectral representation vector and determines a first end point of speech activity when the set of spectral representation vectors diverges from the steady state spectral representation vector.
Claim 34
Dependent Claim
32 words
The apparatus of claim 25, wherein the processor also determines a second end point of speech activity when the set of spectral representation vectors converges towards the steady state spectral representation vector.
Claim 35
Dependent Claim
24 words
The apparatus of claim 26, wherein the processor also determines whether the speech activity more closely resembles a speech codebook or a noise codebook.
Claim 36
Dependent Claim
13 words
The apparatus of claim 25, wherein the spectral representation vectors are autocorrelation vectors.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2000-11-24 | 2001-05-26 | 2001-11-25 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2004-11-24 | 2005-05-26 | 2005-11-25 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2008-11-24 | 2009-05-26 | 2009-11-25 | $7700.00 | Window Closed / Lapsed |