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`Patent Application No. 10/667,26ARCEIVED
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`Attorney Docket No. ALPH.P010X
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`Transmittal of Office Action Response
`Certification ofTransmission Under 37 C.F.R. $1.8
`Transmitted to USPTO Central Facsimile No.
`571-273-8306
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`July 23, 2007
`Date of Transmission
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`JUL 2 3 2007
`Patent
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`See?NeueSeeSeeNee”Nee”See“ee”
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`Uhereby certify that this document, and any other accompanying documentsreferred to herein are being
`transmitted via facsimile to the United States Patent Office to the facsimile mumber and on the date
`indicated above.
`
`BarbaraB. Courtney
`
`,
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`(Print Name of Person Transmitting Facsimile)
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`(Signature of Person Transmitting Pacsiggile)
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`’ Atty. Docket No. ALPH.P010X
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`PATENT
`
`IN THE UNITED STATES PATENT OFFICE
`In Re Patent Application of: .
`
`’ Gregory C. Burnett, et al.
`
`Application No.: 10/667,207
`
`_ Filed: September 18, 2003
`
`Examiner: Lun 8. Lao
`Art Unit:
`2615
`
`|
`
`. For:
`
`VOICE ACTIVITY DETECTION (VAD)-BASED)
`MULTIPLE-MICROPHONE ACOUSTIC NOISE )
`SUPPRESSION
`)
`
`Commissioner for Patents
`P.O. Box 1450
`Alexandria, VA 22313-1450
`RESPONSE TO OFFICE ACTION UNDER37 C.E.R. § 1.111
`
`* Sar:
`
`This is in response to the Office action mailed February 7, 2007. Please enter
`and consider the following amendments and Remarks.
`
`Attorney Docket No. ALPH.PO10XK
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`1
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`Patent Application No. 10/667,207
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`IN THE CLAIMS
`
`(Currently amended) A method for removing noise from acoustic signals,
`I.
`comprising:
`-
`receiving a plurality of acoustic signals, wherein receiving the plurality of
`acoustic signals includes receiving using a plurality of independently located
`microphones;
`
`receiving information on the vibration of humantissue associated with human
`
`voicing activity;
`
`generating at least one first transfer function representative of the plurality of
`acoustic signals upon determining that voicing information is absent from the plurality of
`acoustic signals forat least one specified period of time; and
`
`removing noise from the plurality of acoustic signals using thefirst transfer
`
`function to produceat least one denoised acoustic data stream.
`
`(Original) The method of claim 1, wherein removing noise further comprises:
`2.
`generating at least one second transfer function representative ofthe plurality ofacoustic
`signals upon determining that voicing information is present in the plurality of acoustic
`signals for the at least one specified period of time; and
`removing noise from the plurality of acoustic signals using at least one
`combination ofthe at least onefirst transfer function and the at least one second transfer
`
`function to produce at least one denoised acoustic data stream.
`
`OoCO“AAthBHWwWBe
`aAUW&WH—
`
`10
`
`11
`
`12
`
`—
`
`2
`3
`
`1
`2
`
`(Original) The methodof claim 1, wherein the plurality of acoustic signals
`3.
`includeat least one reflection of at least one associated noise source signal and at least
`onereflection ofat least one acoustic source signal.
`
`(Original) The method of claim 1, wherein receiving the plurality of acoustic
`4.
`signals includes receiving using a plurality of independently located microphones.
`
`Attorney Docket No. ALPH.PO10X
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`2
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`}
`2
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`(Original) The method of claim 2, wherein removing noise further includes
`5.
`generating at least one third transfer function using the at least one first transfer function
`and the at least one second transfer function.
`
`(Original) The method of claim 1, wherein generating the at least onefirst
`6.
`transfer function comprises recalculating the at least one first transfer function during at
`2
`3__least one prespecified interval,
`
`(Original) The method of claim 2, wherein generating the at least one second
`7.
`1
`2 transfer function comprises recalculating the at least one secondtransfer function during
`3
`at least one prespecifiedinterval.
`
`1
`2
`3
`
`1
`
`2
`
`(Original) The method of claim 1, wherein generating the at least one first
`8.
`transfer function comprises use ofat least one technique selected from a group consisting
`of adaptive techniques and recursive techniques.
`
`9,
`
`(Original) The method of claim 1, wherein informationon the vibration of human
`
`tissue is provided by a mechanicalsensor in contact with the skin.
`
`1=10. (Original) The method of claim |, whereininformation on the vibration of human
`
`2
`tissue is provided via at least one sensor selected from amongat Jeast one of an
`3
`accelerometer, a skin surface microphonein physical contact with skin of a user, a human
`4—tissue vibration detector, a radio frequency (RF) vibration detector, andalaser vibration
`detector.
`5
`
`1
`2
`
`1
`2
`
`(Original) The method of claim 1, wherein the human tissue is at least one of on a
`11.
`surface of a head, near the surface of the head, on a surface of a neck, near the surface of
`
`the neck, ona surface of a chest, and near the surface of the chest.
`
`(Currently amended) A method for removing noise from electronic signals,
`42.
`comprising:
`
`ALPH.P010X
`
`3
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`OoOoHYDAUHHRWwW
`
`10
`11
`12.
`
`1
`2
`
`1
`2
`
`2
`
`1
`2
`
`b&bWYN=
`
`. detectingan absence of voiced information during at least one period, wherein,
`detecting includes measuring the vibration of human tissue, wherein detecting the
`plurality of acoustic signals includes detecting using a plurality of independently located
`microphones;
`
`receiving at least one noise source signal duringthe at least one period;
`generating at least one transfer function representative ofthe at least one noise
`source signal;
`receiving at least one composite signal comprising acoustic and noise signals; and
`removing the noise signal from theat least one composite signal usingtheat least
`onetransfer functionto produce at least one denoised acoustic data stream.
`
`(Original) The method of claim 12, wherein theat least one noise sourcesignal
`13.
`includes at least one reflection ofat least one associated noise source signal.
`
`(Original) The method of claim 12, wherein the at least one composite signal
`14.
`includesat least one reflection ofat least one associated composite signal.
`
`15.
`(Original) The method of claim 12, wherein the human tissue is at least one of on
`a surface of a head, near the surface of the head, on a surface of a neck, near the surface
`of the neck, on a surface of a chest, and near the surface of the chest.
`
`(Original) The method of claim 12, wherein detecting includes use of a
`16.
`mechanical sensor in contact with the human tissue.
`
`(Currently amended) The method system of claim 12, wherein detecting includes
`17.
`use of a sensor selected from amongat least one of an accelerometer, a skin surface
`microphone in physical contact with a user, a human tissue vibration detector, a radio
`
`frequency (RF) vibration detector, and a laser vibration detector.
`
`(Original) The method of claim 12, wherein receiving includes receiving the at
`418.
`1
`2_least one noise source signal using at least one microphone.
`
`ALPH.POTOX
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`4
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`(Original) The method ofclaim 18, wherein the at least one microphoneincludes
`19.
`aplurality of independently located microphones.
`
`(Original) The methodof claim 12, wherein removingthe noise signal from the
`20.
`at least one composite signal using the at least one transfer function includes generating
`at Jeast one othertransfer function using the at least one transfer function.
`
`(Original) The methodof claim 12, wherein generating at least one transfer
`21.
`function comprises recalculating the at least one transfer function duringat least one
`" prespecified interval.
`
`(Original) The method of claim 12, wherein generating the at least onc transfer
`22,
`function comprises calculating the at least one transfer function using at least onc
`techniqueselected from a group consisting of adaptive techniques and recursive
`
`technidques.
`
`(Currently amended) A multiple microphone method for removing noise from
`23.
`electronic signals, comprising:
`
`determining at least one unvoicing period during which voiced information is
`
`absent based on vibration of human tissue;
`
`receiving at least one noise signal input during the at least one unvoicing period
`and generating at least one unvoicing transfer function representative of the at least one
`noise signal;
`receiving at least one composite signal comprising acoustic and noise signals; and
`
`removing the noise signal from the at least one composite signal usingthe at least
`unvoicing transfer function to produce at least one denoised acoustic data stream.
`
`(Original) The method of claim 23, wherein producing at least one denoised
`24.
`acoustic data stream further includes:
`.
`
`determining at least one voicing period during which voiced informationis
`
`present;
`
`1
`2
`
`1
`2
`3
`
`1
`2
`
`&WDWN-
`
`woaesHDmHF&FHYPB
`
`—_ So
`
`&YWYN
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`receiving at least one acoustic signal input from at least one signal sensing device
`during the at least one voicing period and generating at least one voicing transfer function
`representative ofthe at least one acoustic signal; and
`removing the noise signal from the at least one composite signal using at least one
`combination of the at least one unvoicing transfer functionand the at least one voicing
`transfer function to produce the denoised acoustic data stream.
`
`25.
`
`(Onginal) The method of claim 23, wherein the human tissuc is at least one of on.
`
` asurface ofa head, near the surface of the head, on a surface of a neck, near the surface
`of the neck, on a surface of a chest, and near the surface of the chest.
`
`26.
`
`(Original) A system for removing noise from the acoustic signals, comprising:
`at least onc receiver that receives at least one acoustic signal;
`at least one sensor that receives humantissue vibration informationassociated
`
`with human voicing activity;
`
`at least one processor coupled amongthe at least one receiver and the at least one
`
`sensor that generates a plurality oftransfer functions, wherein at least one first transfer
`
`functionrepresentative of the at least one acoustic signal is generated in response to a
`determination that voicing information is absent from the at least one acoustic signal for
`at least one specified period of time, wherein noise is removed from the at least one
`
`acoustic signal using the first transfer function to produce at least one denoised acoustic
`data stream.
`
`27.
`
`(Original) The system of claim 26, wherein at least one second transfer function
`
`representative of the at least one acoustic signal is generated in response to a
`determination that voicing information is present in the at least one acoustic signal for the
`at least one specified period oftime, wherein noise is removed from the at least one
`
`acoustic signal using at least one combination ofthe at least one first transfer function
`
`andthe at least one secondtransfer function to produce the at least one denoised acoustic
`data stream.
`
`woOonNKHWT
`
`10
`
`1
`
`2
`
`=O.0mMAIAWHBwWw|vt
`“aAwmBWNH=
`
`ALPH.PO10X
`
`6
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`1.
`2
`
`(Original) The system of claim 26, wherein the sensor includes a mechanical
`28.
`sensor in contact with the skin.
`
`Patent Application No. 10/667,207
`
`(Original) The system of claim 26, wherein the sensor includesat least one of an .
`29,
`accelerometer, a skin surface microphone in physical contactwith skin ofa user, a human
`tissue vibration detector, a radio frequency (RF) vibration detector, anda laser vibration
`detector.
`
`(Original) The system of claim 26, wherein the human tissueis at least one of on
`30.
`a surface of a head, near the surface ofthe head, on a surfaceof a neck, near the surface
`of the neck, on a surface of a chest, and near the surface of the chest.
`
`31.
`
`(Original) The system ofclaim 26, further comprising:
`dividing acoustic data ofthe at least one acoustic signal into a plurality of
`subbands;
`.
`|
`
`removing noise from eachofthe plurality of subbands using the at least onefirst
`transfer function, wherein a plurality ofdenoised acoustic data streams are generated; and
`combining the plurality ofdenoised acoustic data streamsto generate the at
`least one denoised acoustic data stream.
`
`(Original) The system of claim 26, wherein theat least one receiver includes a
`32.
`plurality
`of independently located microphones.
`
`(Original) A system. for removing noise from acoustic signals, comprising at least
`33,
`one processor coupled amongat least one microphone andat least one voicing sensor,
`wherein the at least one voicing sensor detects human tissue vibration associated with
`voicing, wherein an absence ofvoiced information is detected during at least one period
`using the at least one voicing sensor, wherein at least one noise source signal is received
`during the at least one period using the at least one microphone, wherein the at least one
`processor generates at least one transfer function representative of the at least one noise
`
`1
`
`>»WwWbw
`
`—
`
`2
`
`1 2
`
`3.
`
`4
`5
`6
`7
`
`1
`2
`3
`
`1
`
`“SDOWF&FWbh
`
`ALPH.PO1OX
`
`.
`
`7
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`source signal, wherein the at least one microphonereceives at least one composite signal
`comprising acoustic and noise signals, and the at least one processor removesthe noise
`signal from the at least one composite signal using the at least one transfer function to
`produceat least one denoised acoustic data stream.
`
`(Original) The system of claim 33, wherein the human tissueis at least one of on
`34,
`asurface of a head, near the surface of the head, on a surface of a neck, near the surface
`of the neck, on a surface of a chest, and near the surface of the chest.
`
`(Original) A signal processing system coupled amongat least one user and at
`35.
`least one electronic device, wherein the signal processing system includes at least one
`denoising subsystem for removing noise from acoustic signals, the denoising subsystem
`comprising at least one processor coupled among atJeast one receiver and at least one
`sensor, wherein the at least one receiver is coupled to receive at least one acoustic signal,
`wherein the at least one sensor detects human tissue vibration associated with human
`
`voicing activity, wherein the-at least one processor generates a plurality of transfer
`functions, wherein at least one first transfer function representative ofthe at least one
`acoustic signal is generated in response to a determination that voicing informationis
`‘absent from the at least one acousticsignal for at least one specified period oftime,
`wherein noise is removed from the at least one acoustic signal using thefirst transfer
`function to produce at least one.denoised acoustic data stream.
`
`(Original) The system ofclaim 35, wherein at least one second transfer function
`36.
`representative of the at least one acoustic signal is generated in response to a
`determination that voicing information is presentin the at least one acousticsignal,for at
`least one specified period oftime, wherein noise is removed from theat least one acoustic
`signal using at least one combination ofthe at least onefirst transfer function andthe at
`
`least one second transfer function to produceat least one denoised acoustic data stream.
`
`8
`9
`10
`11
`
`1
`2
`3
`
`woOoDTHDtHFFWDYP—
`wzDAanABeWwWNH=
`
`NO
`
`—ma
`
`zi
`
`2
`
`(Original) The system of claim 35, wherein the at least one electronic device
`37.
`includes at least one ofcellular telephones,personal digital assistants, portable
`
`ALPH.P010X
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`communication devices, computers, video cameras, digital cameras, and telematics
`systems.
`
`Patent Application No. 10/667,207
`
`(Original) The system of claim 35, wherein the hurnantissue is at least one of on
`38,
`asurface of a head, near the surface ofthe head, on a surface of a neck, near the surface
`of the neck, on a surface of a chest, and near the surface of the chest.
`
`_3
`4
`
`1
`2
`3
`
`woFNDAHHB&WWH=
`onNAABOBeBD
`
`1
`
`_ So
`
`we _
`
`(Original) A computer readable medium comprising executable instructions
`39.
`which, when
`executed ina processing system, remove noise from received acoustic signals by:
`receiving at least one acoustic signal;
`
`receiving human tissue vibration information associated with human voicing
`activity;
`
`generating at least one first transfer function representative of the at least one
`acoustic signal upon detertnining that voicing information is absent from the at least one
`acoustic signal for at least one specified period of time; and
`
`removing noise from the at least one acoustic signal usingthe at least one first
`transfer function to produceat least one denoised acoustic data stream.
`
`(Original) The medium ofclaim 39, wherein removing noise from received
`840.
`acoustic signals further includes:
`
`generating at least one second transfer function representative ofthe at least one
`acoustic signal upon determining that voicing informationis present in the at least one
`acoustic signal for at least one specified period of time; and
`removing noise from the at least one acoustic signal using at least one
`combination of the at least one first transfer function and the at least one secondtransfer
`function to produceat least one dengised acoustic data stream.
`
`—
`2
`
`(Original) The medium of claim 39, wherein the human tissueis at least one of
`41.
`onasurface of a head, near the surface of the head, on a surface of a neck, near the
`surface of the neck, on a surface of a chest, and near the surface of the chest.
`
`ALPH.P010X
`
`9
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`—
`
`—_ —
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`—
`
`OoCOCOHNDHF&FWDLB
`reNAAFPFWYWH
`
`' Patent Application No. 10/667,207
`
`(Original) An electromagnetic medium comprising executable instructions
`42.
`which, when
`executed in a processing system, remove noise from received acoustic signals by:
`receiving at least one acoustic signal;
`|
`receiving human tissue vibration information associated with human voicing
`activity;
`
`generating at least one first transfer function representative ofthe at least one
`acoustic signal upon determining that voicing information is absent from theat least one
`acoustic signal for at least one specified period of time; and
`removing noise fromthe at least one acoustic signal using the at least onefirst
`transfer function to produce at least one denoised acoustic data stream.
`
`(Original) The medium of claim 42, wherein removing noise from received
`43.
`acoustic signals further includes:
`
`generating at least one second transfer function representative ofthe at least one
`acoustic signal upon determining that voicing information is present in the at least one.
`acoustic signal for at least one specified period of time; and
`removing noise fromthe at least one acoustic signal usingat least one
`combination of the at least one first transfer function and the at least one second transfer
`
`function to produce at least one denoised acoustic data stream.
`
`(Original) The medium ofclaim 42, wherein the human tissueis at least one of
`44.
`1
` onasurface of a head, near the surface of the head, on a surface of a neck, near the
`2
`3. surface of the neck, on a surface of a chest, and near the surface ofthe chest.
`
`ALPH.POIOX
`
`10
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`REMARKS
`
`Claims 1-44 are pending in the application. Claims 1, 12, 17, and 23 have been
`amended. Noclaims have been allowed. Applicants respectfully request entry ofthe
`foregoing amendments and allowanceofthe application as amended.
`
`Petitionfor extension of time
`
`A petition for a three month extension oftime under 37 C.F.R. § 1.136(a) is
`included herewith, as well as the fee under 37 C.F.R. § 1.117(a)(3).
`
`Double Patenting Rejection
`Claims 1-44 were rejected under the judicially created doctrine of obviousness-
`type double patenting as being unpatentable over claims 1-39 of U.S. Patent
`application publication number 2003/0228023 (U.S. Patent Application No.
`10/400,282). Applicants submit herewith a Terminal Disclaimerin compliance with 37
`C.F.R. § 1.130(c), as well as the fee under C.F.R. § 1.20(d). Applicants respectfully
`request withdrawalofthe rejection.
`
`Rejections under 35 U.S.C. § 102
`
`Claims 1-3, 5-18, 20-30, and 33-34 wererejected under 35 U.S.C. § 102(b) as
`being anticipated by Holzrichter (U.S. patent number 5,729,694, hereinafter
`“Holzrichter”). Applicants respectfully traverse the rejection.
`The examiner states in paragraph 5 of the Office action:
`
`.
`aaa
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`5. Clain1-2, 6-18, 20-30 and 93-44 are rejectad under 35 U.S.C. 102(b) as being
`anticipated by Holzrichter (US PAT. 5,729,694),
`Consider clam 1 Holzihter teaches @ melhod for removing noise fram acoustic
`signals, comprising:
`
`.
`
`receiving(ee fig.43, 52) a plurality ofceouatic signals:
`
`rapelving (43) information on the vibrationof human tissueasacclated with human
`
`voicing activity:
`
`generating at least one first transfer function (57) representative of the plurality of
`acoustic signals upon determining thet wolcing information is absent (such as, unyolcs)
`from the plurality ofacoustic signals for at lexst one specified period af time {such as,
`lime frames)}{see col.28 line 38-48); and
`removing noise (removing noise is inherentto speach recognition algorithm to
`extract the best speach feeture and avoid neise) from the plurallty of acoustic signals
`usingthe first transfer (57) function to produce at least one denoised acoustic data
`strearn (60, see col. 15 fine 29-col. 16 fine 3 and col. 60 line 19-30).
`
`Applicants respectfully submit that claims 1-3, 5-18, 20-30, and 33-34 are not
`anticipated by Holzrichter. Holzrichter lacks at least one element of the claims.
`
`Specifically, Holzrichter lacks at least the following elements: transfer function(s); and
`use of more than one microphone. To explain the differences between the claimed
`invention and Holzrichter, and to support Applicants statement that Holzrichter lacks
`the stated clements, Applicants submit the following ananlysis.
`Applicants submit that while Holzrichter does discuss receiving both acoustic
`(microphone-based) and “EM wave”(col. 15, lines 19) based measurements,
`Holzrichter uses only a single microphone. Further, Holzrichter uses the “EM wave”
`only to measure “the conditions of the vocal folds and the glottal tissue surrounding the
`vocalfold structure” (col. 15, lines 26-28). Applicants do not claim to measure the
`conditions of vocal folds or surrounding structure; but rather claim the use of
`physiologically-based device to determine the VAD signal, which is not mentioned in
`Holzrichter. In addition, in contrast to Holzrichter , Applicants claim “recciving a
`plurality of acoustic signals, whereinreceiving the plurality of acoustic signals
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`includes receiving using a plurality of independently located microphones.” (Claim 1
`as amended).
`Holzrichter does not genetate any transfer function as in (57). Rather,
`Holzrichter generates a Fourier Transform, which is a measure of the frequency content
`
`
`of a signal.Inordertogenerateatransfertwosignals(aninputandoutput)function,
`
`(areneeded.)Holzrichter has only one signal and simplytransforms it into the frequency
`domain, which is completely different from, and exclusive of, taking two Signals and
`generating a transfer function. Even the quoted passage at col. 28 lines 38-48 does not
`discuss time frames — it is simply a discussion of how Holzrichter thinks the end of a
`speech period should be calculated when a voiced to unvoiced transition takes place:
`
`In the case that the speech changes from voiced to
`unvoiced, the last glottal open/close period of the voiced
`40 speech sequence has no “next” glottal cycle to use to define
`its end ofperiod. In one approach, the algorithm continually
`tests the Jength of each glottal closed-time in cach time
`frame fer excessive length (e.g. 20% longer than the pre-
`ceding glottal period closure-time). If the period is texted to
`45 betoo long,the algorithrn tenminetes the period and assigns,
`for example, a pglottal-<closure time-doration equal to the
`fractional closure time of the glottal function measured in
`the preceding time frames.
`
`The foregoingis not related to segmenting data into time frames for processing.
`Finally, (57) and (60) along with col. 15 line 29 — col. 16 line3 and col. 60
`lines 19-30 have nothing to do with removing noise. (57) is a Fourier Transform, as
`“noted above, and (60) is a “Vocal tract feature extractor” which is unrelated to present
`claims. Col. 15 lines 29-col. 16 line 3 describes Holzrichter’s perception of how a
`“vocal tract Fourier Transform” would appear (col. 15 line 67-col. 16 line 1). This isto
`' be distinguished as being completely different from a calculating transfer function as
`
`claimed.
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`\
`
`FIG. 5 shows a system in which knowledge of the
`vooalized excitation fuaction is used to decoavolve fhe so
`speech vocal tract transfer function information from mea
`sured acoustic specch output cach time frame. All of the
`information gathered during eachspeech timeframe, inciad-
`img: acoustlts, HM senior informatiog, and deconvolved
`transferfinction information, cam boprocessed, nonwalized, 35
`quantized, and stored (along with control information) in a
`feature vectorrepresenting the spealeer’s voice during ane or
`more speech time fremes. Similar decorvolving procedures
`are used with unvoiced excitation functions. As shown in.
`FIG, 3,an EM sensor contolunit 40 drives a repetition rate. 40
`trigget 41, which delves puise generator 42, which transmits
`one of more pulsesfrom antenna 43. EM sensor control unit
`40. sets the pulse format, dims frame interval, integration,
`times, memory locations, fuaction focms, and controls and
`initializes pulse generator42. Control unit 40 and tipper 41. 43
`aloo antuate switch 45 through delay 44 to range gate
`receivedpulses. Antenna 43.is portioned to direct transmit-
`ted pulses towards. the vocal organs and receive pulses
`reflectedtherefrom.Therecelved pulses pass through switch
`45 and are integmtcd by fatcgrator 46, then amplified by 50
`ammplifier 47, and passod through & high pase filter 48 to 2
`processing tnit 49. Processing anit 49 contains an AD
`converter for digitizing the FIM signals and also includes
`zero location detector, mempary detector. and obtains glottal
`area yorsus tins. The digitized and processed data from unit 35
`49 is stored in memvuty bins $0, from which excitation
`function feature vectors are formed in block $1.
`Simalteneonsly, signals from an.acgustic microphone S¢ me
`dightized by AD converter 53, which is also controlied and
`synchronized by EM sensor control unit 49. Tho digitized 90
`data fromAD sowverter $3 is stored in memory bins$4 from
`which acoustic featare vectors ane formed in block $5. The
`digitized yocal fold data om memory bins 50 is used to
`produce a glottal Fourier transform 56, while the digitized
`acoustic data in memory bin 54 is used 1 produce an 65
`acoustic Fourier transform57. The two Fourier transforms
`56, 57 are decomvolyed in block 53 to produce a vocal tract -
`Fourier transforin 59 whieh is tren fit
`to a prechosen
`Tunetianalformtoformavocaltractfeatarevector in block
`
`Finally, in col. 60 lines 19-30, Holzrichter discusses removing “acoustically
`generated noise” from the “glottal signal” using “Fourier transform techniques”(col.
`60 lines 19-22). Thisis not related to the present claims because:
`1. The noisysignal of Holzrichter is a “glottal signal”, while the claimed noisy
`signal is an acoustic microphonesignal.
`2. Holzrichter does not describe or embody his “Fourier transform techniques”,
`so they are notavailable to be comparedto the claimed techniques.
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`Acoustically gencrated noise can be removed from the
`20 glottal signal by using microphone information to subtract
`thenoise signal, or by using Foucter transform techniques to
`filter out acoustic signals from the glottal motion signals.
`The functio