US5583961A
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US
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Speaker recognition using spectral coefficients normalized with respect to unequal frequency bands
Assignee: British Telecommunications PLC
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Filing: 1993-08-13
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Granted: 1996-12-10
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Expires: 2013-08-13
Abstract
Abstract Apparatus and method for speaker recognition includes generating, in response to a speech signal, a plurality of feature data having a series of coefficient sets, each set having a plurality of coefficients indicating the short term special amplitude in a plurality of frequency bands. The feature data is compared with predetermined speaker reference data, and recognition of a corresponding speaker is indicated in dependence upon such comparison. The frequency bands are unevenly spaced along the frequency axis, and a long term average spectral magnitude of at least one of said coefficients is derived and used for normalizing the at least one coefficient.
Inventors
- 👤 Mark Pawlewski
- 👤 Joseph G. Tang
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-10-29 09:57
CPC Classifications
G; G10; G10L; G10L25/00; G10L25/78; G10L25/87; G10L17/00; G10L17/02
Claims Analysis
Total Claims: 56
Claim 1
Independent Claim
131 words
A method of speaker recognition, said method comprising the steps of: deriving recognition feature data from an input speech signal represented by plural successive frames of digital data for a speech utterance, said recognition feature data comprising a plurality of coefficients each related to speech signal magnitude in a predetermined frequency band; comparing said feature data with predetermined speaker reference data; indicating recognition of a speaker in dependence upon the comparison; said frequency bands being unevenly spaced with respect to frequency, said deriving step including a step of deriving a long term average spectral magnitude extending over plural of said frames of digital data; and processing at least one of said coefficients so as to generate a normalized coefficient in which the effect of said long term magnitude is substantially reduced.
Claim 2
Independent Claim
131 words
A method of speaker recognition, said method comprising the steps of: deriving recognition feature data from an input speech signal represented by plural successive frames of digital data for a speech utterance, said recognition feature data comprising a plurality of coefficients each related to speech signal magnitude in a predetermined frequency band; comparing said feature data with predetermined speaker reference data; indicating recognition of a speaker in dependence upon the comparison; said frequency bands being unevenly spaced with respect to frequency, said deriving step including a step of deriving a long term average spectral magnitude extending over plural of said frames of digital data; and processing at least one of said coefficients so as to generate a normalized coefficient in which the effect of said long term magnitude is substantially reduced.
Claim 3
Dependent Claim
17 words
A method as in claim 1, in which the frequency bands are spaced on a mel-frequency scale.
Claim 4
Dependent Claim
31 words
A method as in claim 1, in which the frequency bands are spaced linearly with respect to frequency below a predetermined limit and logarithmically with respect to frequency above said limit.
Claim 5
Dependent Claim
39 words
A method as in claim 1 in which the deriving step includes a step of generating a logarithm of said magnitude, generating a logarithmic long term average value and subtracting the logarithmic long term average from the logarithmic magnitude.
Claim 6
Dependent Claim
19 words
A method as in claim 1 in which said comparing step time-aligns the feature data with the reference data.
Claim 7
Dependent Claim
17 words
A method as in claim 5, in which the comparing step employs a Dynamic Time Warp process.
Claim 8
Dependent Claim
40 words
A method as in claim 1 further comprises: recognizing a speech start point and a speech end point within said input speech signal; and deriving said long term average over the duration between said start point and said end point.
Claim 9
Dependent Claim
17 words
A method as in claim 1 in which said long term average comprises the long term mean.
Claim 10
Dependent Claim
20 words
A method as in claim 1 in which said long term average comprises a moving average which is periodically updated.
Claim 11
Dependent Claim
27 words
A method as in claim 1 further comprising: inputting a plurality of words one after another, and forming said long term average over all of said words.
Claim 12
Dependent Claim
120 words
Apparatus for speaker recognition which comprises: means for generating a plurality of feature data comprising a series of coefficient sets from a speech signal represented by plural successive frames of digital data for a speech utterance, each set comprising a plurality of coefficients indicating short term spectral magnitude in a plurality of unevenly spaced frequency bands, means for comparing said feature data with predetermined speaker reference data and for indicating recognition of a corresponding speaker in dependence upon said comparison, and means for deriving a long term average spectral magnitude of at least one of said coefficients extending over plural of said frames of digital data and for normalizing the said at least one coefficient by said long term average.
Claim 13
Dependent Claim
120 words
Apparatus for speaker recognition which comprises: means for generating a plurality of feature data comprising a series of coefficient sets from a speech signal represented by plural successive frames of digital data for a speech utterance, each set comprising a plurality of coefficients indicating short term spectral magnitude in a plurality of unevenly spaced frequency bands, means for comparing said feature data with predetermined speaker reference data and for indicating recognition of a corresponding speaker in dependence upon said comparison, and means for deriving a long term average spectral magnitude of at least one of said coefficients extending over plural of said frames of digital data and for normalizing the said at least one coefficient by said long term average.
Claim 14
Dependent Claim
16 words
Apparatus as in claim 11, in which the frequency bands are spaced on a mel-frequency scale.
Claim 15
Dependent Claim
30 words
Apparatus as in claim 11, in which the frequency bands are spaced linearly with respect to frequency below a predetermined limit and logarithmically with respect to frequency above said limit.
Claim 16
Dependent Claim
43 words
Apparatus as in claim 11 in which the means for generating said coefficients are arranged to generate a logarithm of said magnitude, to generate a logarithmic long term average value and to subtract the logarithmic long term average from the logarithmic coefficient magnitude.
Claim 17
Dependent Claim
22 words
Apparatus as in claim 11 in which said means for comparing is arranged to time-align the feature data with the reference data.
Claim 18
Dependent Claim
17 words
Apparatus as in claim 15, in which the means for comparing employs a Dynamic Time Warp process.
Claim 19
Dependent Claim
50 words
Apparatus as in claim 11 further comprising: means for recognizing a start point and an end point within said speech signal, said means for deriving and normalizing is arranged to derive said long term average over the duration of a speech utterance between said start point and said end point.
Claim 20
Dependent Claim
16 words
Apparatus as in claim 11 in which said long term average comprises the long term means.
Claim 21
Dependent Claim
19 words
Apparatus as in claim 11 in which said long term average comprises a moving average which is periodically updated.
Claim 22
Dependent Claim
40 words
Apparatus as in claim 11 arranged for inputting speech signals representing a plurality of words one after another, in which said means for deriving and normalizing is arranged to form said long term average over all of the said words.
Claim 23
Dependent Claim
13 words
Apparatus as in claim 11 adapted to be connected to a telephone network.
Claim 24
Dependent Claim
9 words
A telephone network comprising apparatus as in claim 21.
Claim 25
Dependent Claim
118 words
Apparatus for recognition processing of a voice signal represented by plural successive frames of digital data for a speech utterance, said apparatus comprising: means for deriving recognition data comprising a plurality of signals each related to short term amplitude in a corresponding frequency band of said voice signal said frequency bands being unevenly spaced in the frequency domain, means for performing recognition processing using said recognition data, means for periodically generating or updating a moving long term average spectral amplitude extending over plural of said frames of digital data in said frequency bands; and means for processing feature data based on said recognition data using said long term average to reduce their dependence upon stationary spectral envelope components.
Claim 26
Dependent Claim
118 words
Apparatus for recognition processing of a voice signal represented by plural successive frames of digital data for a speech utterance, said apparatus comprising: means for deriving recognition data comprising a plurality of signals each related to short term amplitude in a corresponding frequency band of said voice signal said frequency bands being unevenly spaced in the frequency domain, means for performing recognition processing using said recognition data, means for periodically generating or updating a moving long term average spectral amplitude extending over plural of said frames of digital data in said frequency bands; and means for processing feature data based on said recognition data using said long term average to reduce their dependence upon stationary spectral envelope components.
Claim 27
Independent Claim
112 words
A method of speaker recognition, said method comprising: generating recognition feature data from an input speech signal, said recognition feature data comprising a plurality of coefficients each related to the speech signal magnitude in a predetermined frequency band, said frequency bands being unevenly spaced along the frequency axis, the step of generating said coefficients including a step of deriving a long term average spectral magnitude and processing at least one of said coefficients so as to generate a normalized coefficient in which the effect of said long term magnitude is substantially reduced; comparing said feature data with predetermined speaker reference data; and indicating recognition of a speaker in dependence upon the comparison.
Claim 28
Independent Claim
112 words
A method of speaker recognition, said method comprising: generating recognition feature data from an input speech signal, said recognition feature data comprising a plurality of coefficients each related to the speech signal magnitude in a predetermined frequency band, said frequency bands being unevenly spaced along the frequency axis, the step of generating said coefficients including a step of deriving a long term average spectral magnitude and processing at least one of said coefficients so as to generate a normalized coefficient in which the effect of said long term magnitude is substantially reduced; comparing said feature data with predetermined speaker reference data; and indicating recognition of a speaker in dependence upon the comparison.
Claim 29
Dependent Claim
17 words
A method as in claim 24 in which the frequency bands are spaced on a mel-frequency scale.
Claim 30
Dependent Claim
27 words
A method as in claim 24 in which the frequency bands are spaced linearly for frequencies below a predetermined limit and logarithmically for frequencies above said limit.
Claim 31
Dependent Claim
41 words
A method as in claim 24 wherein the step of generating said coefficients includes the sub-steps of: generating a logarithm of said magnitude, generating a logarithmic long term average value, and subtracting the logarithmic long term average from the logarithmic magnitude.
Claim 32
Dependent Claim
19 words
A method as in claim 24 wherein said comparison includes time-alignment of the feature data with the reference data.
Claim 33
Dependent Claim
15 words
A method as in claim 28 wherein the comparison employs a Dynamic Time Warp process.
Claim 34
Dependent Claim
40 words
A method as in claim 24 further comprises: recognizing a speech start point and a speech end point within said input speech signal; and deriving said long term average over the duration between said start point and said end point.
Claim 35
Dependent Claim
16 words
A method as in claim 24 wherein said long term average comprises the long term mean.
Claim 36
Dependent Claim
20 words
A method as in claim 24 in which said long term average comprises a moving average which is periodically updated.
Claim 37
Dependent Claim
30 words
A method as in claim 24 including inputting a speech signal representing a plurality of words one after another, and forming said long term average over all of said words.
Claim 38
Dependent Claim
112 words
Apparatus for speaker recognition, said apparatus comprising: means for generating from a speech signal, a plurality of feature data comprising a series of coefficient sets, each set comprising a plurality of coefficients indicating the short term spectral magnitude in a plurality of frequency bands, said frequency bands being unevenly spaced along the frequency axis; means for deriving a long term average spectral magnitude of at lest one of said coefficients; means for normalizing the or each of said at least one coefficient by said long term average; means for comparing said feature data with predetermined speaker reference data; and means for indicating recognition of a corresponding speaker in dependence upon said comparison.
Claim 39
Dependent Claim
112 words
Apparatus for speaker recognition, said apparatus comprising: means for generating from a speech signal, a plurality of feature data comprising a series of coefficient sets, each set comprising a plurality of coefficients indicating the short term spectral magnitude in a plurality of frequency bands, said frequency bands being unevenly spaced along the frequency axis; means for deriving a long term average spectral magnitude of at lest one of said coefficients; means for normalizing the or each of said at least one coefficient by said long term average; means for comparing said feature data with predetermined speaker reference data; and means for indicating recognition of a corresponding speaker in dependence upon said comparison.
Claim 40
Dependent Claim
15 words
Apparatus as in claim 34 wherein the frequency bands are spaced on a mel-frequency scale.
Claim 41
Dependent Claim
26 words
Apparatus as in claim 34 in which the frequency bands are spaced linearly for frequencies below a predetermined limit and logarithmically for frequencies above said limit.
Claim 42
Dependent Claim
40 words
Apparatus as in claim 34 wherein the means for generating said coefficients include means to: generate a logarithm of said magnitude, generate a logarithmic long term average value and subtract the logarithmic long term average from the logarithmic coefficient magnitude.
Claim 43
Dependent Claim
20 words
Apparatus as in claim 34 wherein means for comparing is arranged to time-align the feature data with the reference data.
Claim 44
Dependent Claim
17 words
Apparatus as in claim 38 in which the means for comparing employs a Dynamic Time Warp process.
Claim 45
Dependent Claim
49 words
Apparatus as in claim 34 further comprising: means for recognizing a start point and an end point within said speech signal, in which aid means for normalizing is arranged to derive said long term average over the duration of the utterance between said start point and said end point.
Claim 46
Dependent Claim
15 words
Apparatus as in claim 34 wherein the long term average comprises the long term mean.
Claim 47
Dependent Claim
18 words
Apparatus as in claim 34 wherein said long term average comprises a moving average which is periodically updated.
Claim 48
Dependent Claim
38 words
Apparatus as in claim 34 arranged for inputting a speech signal representing a plurality of words one after another, in which said means for normalizing is arranged to form said long term average over all of said words.
Claim 49
Dependent Claim
13 words
Apparatus as in claim 34 adapted to be connected to a telephone network.
Claim 50
Dependent Claim
9 words
A telephone network comprising apparatus as in claim 44.
Claim 51
Dependent Claim
93 words
Apparatus for recognition processing of a voice signal, said apparatus comprising: means for deriving recognition data comprising a plurality of signals each related to the short term amplitude in a corresponding frequency band of said voice signal, said frequency bands being unevenly spaced in the frequency domain; means for periodically generating or updating a moving long term average spectral amplitude in said frequency bands, means for processing said feature data using said long term average to reduce their dependence upon stationary spectral envelope components; and means for performing recognition processing in dependence thereon.
Claim 52
Dependent Claim
93 words
Apparatus for recognition processing of a voice signal, said apparatus comprising: means for deriving recognition data comprising a plurality of signals each related to the short term amplitude in a corresponding frequency band of said voice signal, said frequency bands being unevenly spaced in the frequency domain; means for periodically generating or updating a moving long term average spectral amplitude in said frequency bands, means for processing said feature data using said long term average to reduce their dependence upon stationary spectral envelope components; and means for performing recognition processing in dependence thereon.
Claim 53
Independent Claim
135 words
A method of speaker recognition comprising: generating recognition feature data from an input speech signal, comparing said feature data with predetermined speaker reference data; and indicating recognition of a speaker in dependence upon the comparison; wherein said recognition feature generating step comprises; identifying a portion of the input speech signal as representing a single contiguous utterance; generating a plurality of coefficients each relating to the signal magnitude in one of a plurality of predetermined frequency bands of an identified portion of the signal, said frequency bands being unevenly spaced in the frequency domain; deriving a long term average spectral magnitude of the coefficients of the single contiguous utterance; and processing at least one of said coefficients so as to generate a normalized coefficient in which the effect of said long term magnitude is substantially reduced.
Claim 54
Independent Claim
135 words
A method of speaker recognition comprising: generating recognition feature data from an input speech signal, comparing said feature data with predetermined speaker reference data; and indicating recognition of a speaker in dependence upon the comparison; wherein said recognition feature generating step comprises; identifying a portion of the input speech signal as representing a single contiguous utterance; generating a plurality of coefficients each relating to the signal magnitude in one of a plurality of predetermined frequency bands of an identified portion of the signal, said frequency bands being unevenly spaced in the frequency domain; deriving a long term average spectral magnitude of the coefficients of the single contiguous utterance; and processing at least one of said coefficients so as to generate a normalized coefficient in which the effect of said long term magnitude is substantially reduced.
Claim 55
Dependent Claim
22 words
A method as in claim 47 wherein the recognition feature generation step is repeated for each successive single contiguous utterance in isolation.
Claim 56
Dependent Claim
19 words
A method as in claim 47 wherein said long term average comprises a running average which is periodically updated.
References Cited (Backward Citations)
US4829578A
Cited
USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 1999-12-10 | 2000-06-10 | 2000-12-10 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2003-12-10 | 2004-06-10 | 2004-12-10 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2007-12-10 | 2008-06-10 | 2008-12-10 | $7700.00 | Window Closed / Lapsed |