Patent US5377301A successfully refreshed from Google Patents.
US5377301A
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Technique for modifying reference vector quantized speech feature signals
Assignee: AT&T Inc
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Filing: 1994-01-21
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Granted: 1994-12-27
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Expires: 2014-01-21
Abstract
Abstract A signal processing arrangement uses a codebook of first vector quantized speech feature signals formed responsive to a large collection of speech feature signals. The codebook is altered by combining the first speech feature signals of the codebook with second speech feature signals generated responsive to later input speech patterns during normal speech processing. A speaker recognition template can be updated in this fashion to take account of change which may occur in the voice and speaking characteristics of a known speaker.
Inventors
- 👤 Aaron E. Rosenberg
- 👤 Frank K.-P. Soong
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-10-28 05:33
CPC Classifications
G; G10; G10L; G10L19/00; G10L19/02; G10L19/032; G10L19/038; H; H03; H03M; H03M7/00; H03M7/30; H03M7/3082
Claims Analysis
Total Claims: 24
Claim 1
Independent Claim
246 words
An arrangement for modifying a codebook of vector quantized speech feature signals for speaker verification or adaptation to the voice of a particular speaker comprising: means for storing a set of vector quantized feature signals q(i), i=1, 2, . . . , K, where K is the number of vector quantized feature signals in said set, and a set of occupancy signals n(i) each corresponding to one of said vector quantized feature signal q(i); means for receiving an input pattern; means for analyzing said input pattern to generate a set of input feature vector signals v(t), t=1,2, . . . , M, where M is the number of vector-quantized feature signals in an input pattern; means responsive to said set of input feature signals and said set of vector quantized feature signals for classifying each input feature signal v(t) as one of said set if vector quantized feature signals q(i); means responsive to the classification of each input feature signal as one of said vector quantized feature signals for generating an occupancy signal m(i) corresponding to the count of input feature signals classified as each one of said vector quantized feature signals q(i); and means for modifying said set if vector quantized feature vector signals, q(i), to produce a modified set of vector quantized feature vector signals, q'(i), based on said classified input feature vector signals, said input feature occupancy signals, said vector quantized feature signals, and said occupancy signals of said vector quantized feature signals
Claim 2
Dependent Claim
246 words
An arrangement for modifying a codebook of vector quantized speech feature signals for speaker verification or adaptation to the voice of a particular speaker comprising: means for storing a set of vector quantized feature signals q(i), i=1, 2, . . . , K, where K is the number of vector quantized feature signals in said set, and a set of occupancy signals n(i) each corresponding to one of said vector quantized feature signal q(i); means for receiving an input pattern; means for analyzing said input pattern to generate a set of input feature vector signals v(t), t=1,2, . . . , M, where M is the number of vector-quantized feature signals in an input pattern; means responsive to said set of input feature signals and said set of vector quantized feature signals for classifying each input feature signal v(t) as one of said set if vector quantized feature signals q(i); means responsive to the classification of each input feature signal as one of said vector quantized feature signals for generating an occupancy signal m(i) corresponding to the count of input feature signals classified as each one of said vector quantized feature signals q(i); and means for modifying said set if vector quantized feature vector signals, q(i), to produce a modified set of vector quantized feature vector signals, q'(i), based on said classified input feature vector signals, said input feature occupancy signals, said vector quantized feature signals, and said occupancy signals of said vector quantized feature signals
Claim 3
Dependent Claim
24 words
An arrangement for modifying a codebook of vector quantized feature signals according to claim 1 wherein said input pattern comprises an unidentified input pattern.
Claim 4
Dependent Claim
121 words
An arrangement for modifying a codebook of vector quantized feature signals according to claim 2 wherein said vector quantized feature signal modifying means comprises: means responsive to each of said vector quantized feature signal q(i) and to each corresponding one of said vector quantized feature occupancy signals n(i) for forming a weighted vector quantized feature signal; means responsive to each of said input feature signals v(t) classified as one of vector quantized feature signals q(i) and a corresponding one of occupancy signals m(i) for forming a weighted input feature vector signal; and means responsive to said weighted vector quantized feature signal; and said weighted input feature vector signal for generating one of said modified set of vector quantized feature signals q'(i).
Claim 5
Dependent Claim
90 words
An arrangement for modifying a codebook of vector quantized feature vector signals according to claim 2, wherein said modifying means comprises means for forming a signal corresponding to q'(i)=[n(i)q(i)+p(i)]/[n(i)+m(i)], for each value of i, where each n(i)q(i) is a weighted codebook vector quantized feature signal, each n(i) is occupancy signal for each said codebook vector quantized signal q(i), each p(i) is a weighted input feature signal classified as the corresponding one of the vector quantized feature signals q(i), and each m(i) is the occupancy signal for said input feature signal.
Claim 6
Dependent Claim
42 words
An arrangement for modifying a codebook of vector quantized feature vector signals according to claim 4 further comprising: means responsive to said vector quantized feature occupancy signal and said input feature signal occupancy signal for modifying said vector quantized feature occupancy signal.
Claim 7
Dependent Claim
107 words
An arrangement for modifying a codebook of vector quantized feature vector signals according to claim 5 wherein said vector quantized feature occupancy signal modifying means comprises: means for forming signals corresponding to n'(i)=n(i)+m(i)-M.sub.tot /K where each n'(i) is the modified vector quantized feature occupancy signal, each n(i) is the feature occupancy signal of the codebook ith feature vector signal, each m(i) is the occupancy signal for a corresponding one of the input feature vector signals classified as the ith codebook feature vector signal, M tot is the total number of input feature vector signals, and K is the total number of the codebook quantized feature vector signals.
Claim 8
Dependent Claim
83 words
An arrangement for modifying a codebook of vector quantized feature vector signals according to claim 2 wherein said modifying means comprises forming a signal corresponding to q'(i)=(λ)q(i)+(1-λ)p(i)/m(i) for each value of i, where each p(i) is the weighted input feature signal classified as the corresponding one of the vector quantized feature signals q(i) and each m(i) is the occupancy signal for said input feature signal, m(i)<<n(i), and λ is a relative weighting factor which attributes substantially greater significance to n(i) than to m(i).
Claim 9
Dependent Claim
41 words
An arrangement for modifying a codebook of quantized feature vector signals according to claim 7 further comprising: means for modifying said vector quantized feature occupancy signals responsive to said vector quantized feature occupancy signals and said input feature signal occupancy signals.
Claim 10
Dependent Claim
37 words
An arrangement for modifying a codebook of vector quantized feature signals according to claim 8 wherein said vector quantized feature occupancy signal modifying means comprises: means for forming signals corresponding to n'(i)=λn(i)+(1-λ)m(i) for each value of is.
Claim 11
Dependent Claim
40 words
An arrangement for modifying a codebook of vector quantized feature signals according to claim 1, 3, 4, 5, 6, 7, 8 or 2 wherein each feature signal is a speech feature signal and each input pattern is a speech signal.
Claim 12
Dependent Claim
218 words
In a signal processing arrangement having a stored codebook of a set of vector quantized speech feature signals q(i) i=1, 2, . . . , K, where K is the number of vector quantized feature signals in said set, and occupancy signals n(i) each corresponding to one of said vector quantized feature signals, a method for modifying the codebook of vector quantized feature signals for speaker verification or adaptation to the voice of a particular speaker comprising the steps of: receiving an input pattern; analyzing said input pattern to generate a set of input feature vector signals v(t), t=1, 2, . . . , M, where M is the number of vector-quantized feature signals in an input pattern; classifying each input feature vector signal v(t) as one of said set of vector quantized feature signals q(i) responsive to said input feature signals and said set of vector quantized feature signals; generating an occupancy signal m(i) corresponding to the count input feature vector signals classified as respective ones of said vector quantized feature signals q(i) responsive to the classifying step; and modifying said set of vector quantized feature vector signals, q(i), based on said classified input feature vector signals, said input feature occupancy signals, said vector quantized feature signals and said occupancy signals of said vector quantized feature signals.
Claim 13
Dependent Claim
218 words
In a signal processing arrangement having a stored codebook of a set of vector quantized speech feature signals q(i) i=1, 2, . . . , K, where K is the number of vector quantized feature signals in said set, and occupancy signals n(i) each corresponding to one of said vector quantized feature signals, a method for modifying the codebook of vector quantized feature signals for speaker verification or adaptation to the voice of a particular speaker comprising the steps of: receiving an input pattern; analyzing said input pattern to generate a set of input feature vector signals v(t), t=1, 2, . . . , M, where M is the number of vector-quantized feature signals in an input pattern; classifying each input feature vector signal v(t) as one of said set of vector quantized feature signals q(i) responsive to said input feature signals and said set of vector quantized feature signals; generating an occupancy signal m(i) corresponding to the count input feature vector signals classified as respective ones of said vector quantized feature signals q(i) responsive to the classifying step; and modifying said set of vector quantized feature vector signals, q(i), based on said classified input feature vector signals, said input feature occupancy signals, said vector quantized feature signals and said occupancy signals of said vector quantized feature signals.
Claim 14
Dependent Claim
63 words
In a signal processing arrangement having a stored codebook of vector quantized feature signals q(i) i=1, 2, . . . , K and a set of occupancy signals n(i) each corresponding to one of said vector quantized feature signals, a method for modifying the codebook of vector quantized feature signals according to claim 11 wherein said input pattern comprises an unidentified input pattern.
Claim 15
Dependent Claim
143 words
In a processing arrangement having a stored codebook of vector quantized feature signals q(i)i=1, 2, . . . , K and a set of occupancy signals n(i) each corresponding to one of said vector quantized feature signals, a method for modifying the codebook of vector quantized feature signals according to claim 12 wherein said vector quantized feature signal modifying step comprises: forming a weighted vector quantized feature signal responsive to each of said vector quantized feature signals q(i) and each of said vector quantized feature occupancy signals n(i); forming a weighted input feature signal responsive to each of said input feature signals n(t) classified as vector quantized feature signals q(i); and generating a set of modified vector quantized signals q'(i) responsive to said weighted vector quantized feature signal and said weighted input feature signal for each of said vector quantized feature signals q(i).
Claim 16
Dependent Claim
120 words
In a signal processing arrangement having a stored codebook of a set of vector quantized feature signals q(i) i=1, 2, . . . , K and a set of occupancy signals n(i) each corresponding to one of said vector quantized feature signals, a method for modifying the codebook of vector quantized feature signals according to claim 12 wherein said generating step comprises means for forming a signal corresponding to q'(i)=[n(i )q(i)+p(i)]/[n(i)+m(i)], for each value of i, where n(i)q(i) is the set of weighted codebook vector quantized feature signals, p(i) is the set of weighted input feature signals each classified as one of the vector quantized feature signals q(i), and each m(i) is the occupancy signal for said input feature signal.
Claim 17
Dependent Claim
90 words
In a signal processing arrangement having a stored codebook of a set of vector quantized feature signals q(i) i=1, 2, . . . , K and a set of occupancy signals n(i) each corresponding to one of said vector quantized feature signals, a method for modifying the codebook of vector quantized feature signals according to claim 14 further comprising the step of: modifying each of said vector quantized feature occupancy signals responsive to each of said vector quantized feature occupancy signals and each of said input feature signal occupancy signals.
Claim 18
Dependent Claim
140 words
In a signal processing arrangement having a stored codebook of a set of vector quantized feature signals q(i) i=1, 2. . . , K and a set of occupancy signals n(i) each corresponding to one of said vector quantized feature signals, a method for modifying the codebook of vector quantized feature signals according to claim 15 wherein said vector quantized feature occupancy signal modifying step comprises: forming a set of signals corresponding to n'(i)=n(i)+m(i)-M.sub.tot /K where n'(i) is the the set of modified vector quantized feature occupancy signals, n(i) is the feature occupancy signals of the codebook ith feature vector signals, m(i) is the set of occupancy signals for input pattern signals classified as respective ith codebook feature, M tot is the total number of input feature signals, and K is the total number of the codebook quantized feature signals.
Claim 19
Dependent Claim
119 words
In a signal processing arrangement having a stored codebook of a set of vector quantized feature signals q(i) i=1, 2, . . . , K and a set of occupancy signals n(i) corresponding each to one of said vector quantized feature signals, a method for modifying the codebook of vector quantized feature signals according to claim 12 wherein said generating comprises forming a signal corresponding to q'(i)=(λ)q(i)+(1-λ)p(i)/m(i) for each value of i, where each p(i) is the weighted input feature signal classified as one of the vector quantized feature signals q(i), each m(i) is the occupancy signal for said input feature signal, m(i)<<n(i), and λ a relative weighting factor which attributes substantially greater significance to n(i) than to m(i).
Claim 20
Dependent Claim
87 words
In a signal processing arrangement having a stored codebook of a set of vector quantized feature signals q(i) i=1, 2, . . . , K and a set of occupancy signals n(i) each corresponding to one of said vector quantized feature signals, a method for modifying the codebook of vector quantized feature signals according to claim 17 further comprising the step of: modifying each said vector quantized feature occupancy signal responsive to each said vector quantized feature occupancy signal and each said input feature signal occupancy signal.
Claim 21
Dependent Claim
128 words
In a signal processing arrangement having a stored codebook of a set of vector quantized feature signals q(i) i=1, 2, . . . , K and a set of occupancy signals n(i) each corresponding to one of said vector quantized feature signals, a method for modifying the codebook of vector quantized feature signals according to claim 18 wherein said vector quantized feature occupancy signal modifying step comprises: forming a set of signals corresponding to n'(i)=λn(i)+(1-λ)m(i) where n'(i) is the set of modified vector quantized feature occupancy signals, n(i) is the set of feature occupancy signals of the codebook ith feature signals, m(i) is the set of occupancy signals for input feature signals classified as the ith codebook feature signals, and λ is n(i)/(n(i)+m(i)), for each value of i.
Claim 22
Dependent Claim
41 words
An arrangement for modifying a codebook of vector quantized feature signals according to claims 11, 13, 14, 15, 16, 17, 18, 19 or 12 wherein each feature signal is a speech feature signal and each input pattern is a speech signal.
Claim 23
Dependent Claim
206 words
In a signal processing arrangement having a stored codebook of a set of vector quantized feature signals q(i) i=1, 2, . . . K, where K is the number of vector quantized feature signals in said set, and occupancy signals n(i) each corresponding to one of said vector quantized feature signals, a method for modifying the codebook of vector quantized feature signals, the method comprising the steps of: receiving an input pattern; analyzing said input pattern to generate a set of input feature vector signals v(t), t=1, 2, . . . , M, where M is the number of vector-quantized feature signals in an input pattern; classifying each input feature vector signal v(t) as one of said set of vector quantized feature signals q(i) responsive to said input feature signals and said set of vector quantized feature signals; generating an occupancy signal m(i) corresponding to the count input feature vector signals classified as respective ones of said vector quantized feature signals q(i) responsive to the classifying step; and modifying said set of vector quantized feature vector signals, q(i), based on said classified input feature vector signals, said input feature occupancy signals, said vector quantized feature signals and said occupancy signals of said vector quantized feature signals.
Claim 24
Dependent Claim
206 words
In a signal processing arrangement having a stored codebook of a set of vector quantized feature signals q(i) i=1, 2, . . . K, where K is the number of vector quantized feature signals in said set, and occupancy signals n(i) each corresponding to one of said vector quantized feature signals, a method for modifying the codebook of vector quantized feature signals, the method comprising the steps of: receiving an input pattern; analyzing said input pattern to generate a set of input feature vector signals v(t), t=1, 2, . . . , M, where M is the number of vector-quantized feature signals in an input pattern; classifying each input feature vector signal v(t) as one of said set of vector quantized feature signals q(i) responsive to said input feature signals and said set of vector quantized feature signals; generating an occupancy signal m(i) corresponding to the count input feature vector signals classified as respective ones of said vector quantized feature signals q(i) responsive to the classifying step; and modifying said set of vector quantized feature vector signals, q(i), based on said classified input feature vector signals, said input feature occupancy signals, said vector quantized feature signals and said occupancy signals of said vector quantized feature signals.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
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| 3.5 Years (Year 4) | 1997-12-26 | 1998-06-27 | 1998-12-27 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2001-12-26 | 2002-06-27 | 2002-12-27 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2005-12-26 | 2006-06-27 | 2006-12-27 | $7700.00 | Window Closed / Lapsed |