Paper No. 1
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`UNITED STATES PATENT AND TRADEMARK OFFICE
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`____________________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
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`____________________
`
`
`
`
`
`APPLE INC.
`Petitioner,
`
`v.
`
`ANDREA ELECTRONICS INC.,
`Patent Owner.
`
`Patent No. 6,363,345
`Issued: March 26, 2002
`Filed: February 18, 1999
`Inventors: Joseph Marash, et al.
`Title: SYSTEM, METHOD AND APPARATUS FOR CANCELLING NOISE
`
`____________________
`
`Inter Partes Review No. IPR2017-00627
`__________________________________________________________________
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`Petition for Inter Partes Review of
`U.S. Patent No. 6,363,345
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`Petition in IPR2017-00627
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`U.S. Patent No. 6,363,345
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`Table of Contents
`
`I.
`
`Introduction .................................................................................................... 1
`
`II. Regulatory Information ................................................................................ 2
`A. Certification that Petitioner May Contest the ’345 Patent
`(§ 42.104(a)) .......................................................................................... 2
`Identification of Challenged Claims (§ 42.104(b)) ........................... 2
`Fee for Inter Partes Review (§ 42.15(a)) ........................................... 4
`
`B.
`C.
`
`III. The ’345 Patent and Background Technology ............................................ 4
`A.
`Background Technologies ................................................................... 4
`1.
`Audio Signal Processing ............................................................. 4
`2.
`Spectral Subtraction and Boll ..................................................... 7
`The ’345 Patent Disclosure ................................................................. 8
`Effective Filing Date .......................................................................... 12
`Person of Ordinary Skill in the Art ................................................. 12
`
`B.
`C.
`D.
`
`IV. Claim Construction ..................................................................................... 12
`A.
`“magnitude” ....................................................................................... 13
`B.
`“frequency spectrum generator” / “generating the frequency
`spectrum” ........................................................................................... 14
`“threshold detector for setting a threshold… and for detecting” . 14
`“generating a noise canceling signal for canceling noise” ............. 15
`“current minimum value” ................................................................ 16
`“future minimum value” .................................................................. 17
`
`C.
`D.
`E.
`F.
`
`V. Analysis of the Patentability of the ’345 Patent ........................................ 18
`A.
`Introduction ....................................................................................... 18
`1.
`Illustrative Claim....................................................................... 18
`2.
`Index of Grounds ...................................................................... 19
`B. Helf Anticipates Claims 1-7, 9-11, 13-14, 21, 23, 38-41, and 43 .... 20
`1.
`Overview of Helf ...................................................................... 20
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`2.
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`Helf Anticipates Claims 1-7, 9-11, 13-14, 21, 23, 38-41, and 4323
`a)
`Independent Claim 38 ..................................................... 23
`b)
`Independent Claim 1 ....................................................... 27
`c)
`Claims 2-3, 13-14, 21, and 23 ........................................ 29
`d)
`Claims 4-7, 9-11, 39-41, and 43 ..................................... 32
`C. Helf Renders Claims 1-7, 9-11, 13-14, 21, 23, 38-41, and 43
`Obvious ............................................................................................... 38
`D. Helf and Martin Render Claims 6, 8-9, 12, 25, 42, and 46 Obvious41
`1. Martin ........................................................................................ 41
`2.
`Overview of Martin ................................................................... 42
`3.
`The Skilled Person Would Have Considered Helf with Martin43
`4.
`Helf and Martin Would Have Rendered Claims 6, 8-9, 12, 25,
`and 46 Obvious ......................................................................... 44
`a)
`Claim 6 ............................................................................ 45
`b)
`Claim 8 ............................................................................ 46
`c)
`Claim 9 ............................................................................ 48
`d)
`Claims 12 and 42 ............................................................ 49
`e)
`Claim 25 and 46 .............................................................. 51
`E. Helf and Boll Render Claims 17-20 and 47 Obvious ..................... 52
`1.
`Overview of Boll ....................................................................... 52
`2.
`The Skilled Person Would Have Considered Helf with Boll ... 53
`3.
`Claims 17-20 and 47 Are Obvious ........................................... 55
`F. Helf and Arslan Render Claims 15-16 Obvious ............................. 57
`1.
`Overview of Arslan ................................................................... 57
`2.
`A Skilled Person Would Have Considered Helf with Arslan ... 59
`3.
`Claims 15-16 ............................................................................. 60
`G. Helf, Boll, and Arslan Render Claim 24 Obvious .......................... 61
`H. Helf and Uesugi Render Claim 22 Obvious .................................... 64
`1.
`Overview of Uesugi .................................................................. 64
`2.
`Helf and Uesugi Render Claim 22 Obvious ............................. 65
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`I.
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`J.
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`Helf, Martin, and Uesugi Render Claims 44-45 Obvious .............. 66
`1.
`Claim 44 .................................................................................... 66
`2.
`Claim 45 .................................................................................... 66
`No Secondary Considerations Exist ................................................ 67
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`VI. Conclusion .................................................................................................... 67
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`TABLE OF AUTHORITIES
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`Cases
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`Page(s)
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`Cuozzo Speed Techs., LLC v. Lee,
`136 S. Ct. 2131 (2016) ........................................................................................ 12
`
`Ericsson, Inc. v. Intellectual Ventures I LLC,
`IPR2014-00527, Paper 41 (May 18, 2015) .................................................. 41, 52
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`LG Elecs., Inc. v. Straight Path IP Grp., Inc.,
`IPR2015-00196, Paper 20 (May 15, 2015) .......................................................... 2
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`Vivid Techs., Inc. v. Am. Sci. & Eng’g, Inc.,
`200 F.3d 795 (Fed. Cir. 1999) ............................................................................ 13
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`
`
`Statutes
`
`35 U.S.C. § 102(b) ............................................................................................passim
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`Other Authorities
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`37 C.F.R. § 42.104(b) ................................................................................................ 2
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`37 CFR § 42.100(b) ................................................................................................. 12
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`Exhibit List
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`1006
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`1007
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`1008
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`1009
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`Exhibit # Reference Name
`1001
`U.S. Patent No. 6,363,345
`1002
`U.S. Patent No. 6,363,345 File History
`1003
`[Reserved]
`1004
`Declaration of Bertrand Hochwald
`1005
`H. G. Hirsch and C. Ehricher, “Noise estimation techniques for
`robust speech recognition,” Proc. IEEE Int. Conf. Acoustics,
`Speech, Signal Processing, vol. 1, pp. 153 -156, 1995 (“Hirsch”)
`Rainer Martin, “An Efficient Algorithm to Estimate the
`Instantaneous SNR of Speech Signals,” Proc. Eurospeech, pp.
`1093-96, 1993 (“Martin”)
`Letter from Technische Informationsbibliothek re: Proc.
`Eurospeech 1993 (2 Jan. 2017)
`Proc. Eurospeech 1993 Vol. 2 Table of Contents from Technische
`Informationsbibliothek
`Steven F. Boll, “Suppression of Acoustic Noise in Speech Using
`Spectral Subtraction,” IEEE Transactions on Acoustics, Speech,
`and Signal Processing, Vol. ASSP-27, No. 2, April 1979 (“Boll”)
`U.S. Patent No. 5,550,924 to Helf (“Helf”)
`U.S. Patent No. 5,706,395 to Arslan (“Arslan”)
`Excerpts from Deller et al., Discrete-Time Processing of Speech
`Signals (1993)
`Excerpt from Merriam-Webster Dictionary (1993)
`Excerpts from Oppenheim and Willsky, Signals and Systems
`(1997)
`U.S. Patent No. 5,459,683 to Uesugi
`Lim and Oppenheim, “Enhancement and Bandwidth Compression
`of Noisy Speech,” Proceedings of the IEEE, vol. 67, no. 12, pp.
`1586-1604, December 1979
`Affidavit of Service in Andrea Elecs. v. Apple Inc., EDNY
`In the Matter of Certain Audio Processing Hardware and
`Software and Products Containing the Same, Inv. No. 337-TA-
`
`1010
`1011
`1012
`
`1013
`1014
`
`1015
`1016
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`1017
`1018
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`1019
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`1020
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`Exhibit # Reference Name
`949, Claim Construction Order (U.S.I.T.C. Jan. 27, 2016) (“949
`CC Order”)
`In the Matter of Certain Audio Processing Hardware and
`Software and Products Containing Same, Inv. No. 337-TA-949,
`Complainant Andrea Electronics Corp.’s Initial Claim
`Construction Brief (U.S.I.T.C. Oct. 19, 2015) (“Andrea CC Br.”)
`In the Matter of Certain Audio Processing Hardware and
`Software and Products Containing Same, Inv. No. 337-TA-949,
`Commission Investigative Staff’s Initial Markman Brief
`(U.S.I.T.C. Oct. 19, 2015) (“OUII CC Br.”)
`Letter from the parties in 337-TA-949 informing ALJ they agreed
`to certain constructions (Nov. 10, 2015) (prior litigation)
`In the Matter of Certain Audio Processing Hardware, Software,
`and Products Containing The Same, Inv. No. 337-TA-1026,
`Verified Complaint Against Apple Inc. and Samsung Inc. Under
`Section 337 of the Tariff Act of 1930, as Amended (U.S.I.T.C.
`Sept. 19, 2016
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`vii
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`1021
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`1022
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`U.S. Patent No. 6,363,345
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`Petitioner’s Mandatory Notices
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`A. Real Party in Interest (§42.8(b)(1))
`
`The real party in interest of this petition pursuant to § 42.8(b)(1) is Apple
`
`Inc. (“Apple”) located at One Infinite Loop, Cupertino, CA 95014.
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`B. Other Proceedings (§42.8(b)(2))
`
`1.
`
`Patents and Applications
`
`U.S. Patent No. 6,363,345 (“’345 patent”) is not related to any issued patents
`
`or currently pending applications. U.S. Appl. No. 09/385,996 claimed priority to
`
`the application that became the ’345 patent, but was abandoned.
`
`2.
`
`Related Litigation
`
`The ’345 patent has been asserted in the following litigations:
`
`• Andrea v. Apple Inc., Action No. 2-16-cv-05220 (pending);
`
`• Andrea v. Samsung Elec. Co., Action No. 2-16-cv-05217 (pending);
`
`• Andrea v. Hewlett-Packard Co., Action No. 2-15-cv-00208 (terminated);
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`• Andrea v. Dell Inc., Action No. 2-15-00209 (terminated);
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`• Andrea v. Acer Inc., Action No. 2-15-cv-00210 (terminated);
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`• Andrea v. Toshiba Corp., Action No. 2-15-cv-00211 (terminated);
`
`• Andrea v. Lenovo Holding Co., Inc., Action No. 2-15-cv-00212
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`(terminated);
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`• Andrea v. ASUSTeK Computer Inc., Action No. 2-15-cv-00214
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`(terminated); and
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`• Andrea v. Realtek Semiconductor Corp., Action No. 2-15-cv-00215
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`(terminated).
`
`The ’345 patent has been asserted against Petitioner Apple Inc. in the
`
`following administrative proceeding before the ITC:
`
`• 337-TA-1026 (Apple Inc. and Samsung Inc., respondents) (pending).
`
`The ’345 patent has been asserted against other entities in the following
`
`administrative proceedings before the ITC:
`
`• 337-TA-949 (Waves Audio; ASUS Computer Int’l Inc.; Acer Am. Corp.;
`
`Acer Inc.; Dell Inc.; Hewlett-Packard Co.; Lenovo (United States) Inc.;
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`Lenovo Group Ltd.; Lenovo Holding Co., Inc.; Realtek Semiconductor
`
`Corp.; Toshiba Am. Info. Sys., Inc.; Toshiba Am., Inc.; and Toshiba
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`Corp., respondents) (terminated); and
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`• 337-TA-3053 (ASUS Computer Int’l Inc.; ASUSTeK Computer Inc.;
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`Acer Am. Corp.; Acer Inc.; Dell Inc.; Hewlett-Packard Co.; Lenovo
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`(United States) Inc.; Lenovo Group Ltd.; Lenovo Holding Co., Inc.;
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`Realtek Semiconductor Corp.; Toshiba Am. Info. Sys., Inc.; Toshiba
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`Am., Inc.; and Toshiba Corp., respondents) (terminated).
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`3.
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`Patent Office Proceedings
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`The ’345 patent is the subject of IPR2017-00626, filed by Apple
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`concurrently with this petition.
`
`The ’345 patent was the subject of the following proceedings before the
`
`Office:
`
`• Realtek Semiconductor Corp. v. Andrea Elecs. Corp, IPR2015-01394;
`
`• Realtek Semiconductor Corp. v. Andrea Elecs. Corp, IPR2015-01395;
`
`• Waves Audio, Ltd. v. Andrea Elecs. Corp, IPR2016-00459.
`
`C. Lead and Backup Lead Counsel (§42.8(b)(3))
`
`Lead Counsel is: Jeffrey P. Kushan (Reg. No. 43,401), jkushan@sidley.com,
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`(202) 736-8914. Back-Up Lead Counsel are: Steven S. Baik (Reg. No. 42,281),
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`sbaik@sidley.com, (650) 565-7016; and Thomas A. Broughan III (Reg. No.
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`66,001), tbroughan@sidley.com, (202) 736-8314.
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`D.
`
`Service Information (§42.8(b)(4))
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`Service on Petitioner may be made by e-mail (iprnotices@sidley.com), mail
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`or hand delivery to: Sidley Austin LLP, 1501 K Street, N.W., Washington, D.C.
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`20005. The fax number for lead and backup lead counsel is (202) 736-8711.
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`I.
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`Introduction
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`The ’345 patent is generally directed to methods and systems for reducing or
`
`removing noise from an audio signal. It uses a well-known and widely used
`
`technique called “spectral subtraction” first described in a paper by Steven Boll in
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`1979. Ex. 1001, 1:58-2:1 (citing Ex. 1009 (Boll)). At a high level, spectral
`
`subtraction works by taking a noisy audio signal, separating the signal into its
`
`different frequency components, estimating the noise present in each frequency
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`component, subtracting the estimated noise value from the magnitude of frequency
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`component, and recombining the frequency components back into a single signal.
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`The ’345 patent portrays itself as an improvement to the spectral subtraction
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`technique described in Boll. But in the two decades between Boll’s publication in
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`1979 and the 1999 effective filing date of the ’345 patent, many others had
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`improved Boll’s spectral subtraction technique, including by adding the
`
`functionality that the ’345 patent portrays as inventive. For example, Helf
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`describes a spectral subtraction technique that uses a noise estimation process to
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`set a threshold for each frequency component and detect noise. The system in Helf
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`is indistinguishable from the independent claims and many of the dependent
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`claims. And while certain distinctions exist between some of the dependent claims
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`and Helf, none of those represents a patentable distinction over Helf in view of
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`other prior art. Accordingly, the Board should institute trial and cancel the
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`challenged claims of the ’345 patent.
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`II. Regulatory Information
`A. Certification that Petitioner May Contest the ’345 Patent
`(§ 42.104(a))
`Petitioner certifies that the ’345 patent is available for inter partes review.
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`Petitioner also certifies it is not barred or estopped from requesting inter partes
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`review of the claims of the ’345 patent. Neither Petitioner, nor any party in privity
`
`with Petitioner, has filed a civil action challenging the validity of any claim of the
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`’345 patent. The ’345 patent has not been the subject of a prior inter partes review
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`by Petitioner or a privy of Petitioner.
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`Petitioner certifies this petition for inter partes review is timely filed as it
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`was filed less than one year after November 1, 2016, the date Petitioner was first
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`served with a complaint alleging infringement of a claim of the ’345 patent. See
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`35 U.S.C. § 315(b); Ex. 1017. Petitioner was served with an ITC complaint no
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`earlier than September 19, 2016, (Ex. 1022), but administrative complaints do not
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`start the one year period of § 315(b). LG Elecs., Inc. v. Straight Path IP Grp., Inc.,
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`IPR2015-00196, Paper 20 at 7-9 (May 15, 2015).
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`Identification of Challenged Claims (§ 42.104(b))
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`B.
`Petitioner challenges claims 1-25 and 38-47 based on the following grounds.
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`(i) Claims 1-7, 9-11, 13-14, 21, 23, 38-41, and 43 are anticipated under
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`35 U.S.C. § 102 based on U.S. Patent No. 5,550,924 to Helf (“Helf”) (Ex. 1010).
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`(ii) Claims 1-7, 9-11, 13-14, 21, 23, 38-41, and 43 are obvious under 35
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`U.S.C. § 103 based on Helf in view of the knowledge of a person ordinary skill in
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`the art.
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`(iii) Claims 6, 8-9, 12, 25, 42, and 46 are obvious under § 103 based on
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`Helf and Rainer Martin, “An Efficient Algorithm to Estimate the Instantaneous
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`SNR of Speech Signals,” Proc. Eurospeech, 1093-96, 1993 (“Martin”) (Ex. 1006).
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`(iv) Claims 17-20 and 47 are obvious under § 103 based on Helf and
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`Steven F. Boll, “Suppression of Acoustic Noise in Speech Using Spectral
`
`Subtraction,” IEEE Transactions on Acoustics, Speech, and Signal Processing,
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`Vol. ASSP-27, No. 2, 113-20, April 1979 (“Boll”) (Ex. 1009).
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`(v) Claims 15-16 are obvious under § 103 based on Helf and U.S. Patent
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`No. 5,706,395 to Arslan (“Arslan”) (Ex. 1011).
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`(vi) Claim 24 is obvious under § 103 based on Helf, Boll, and Arslan.
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`(vii) Claim 22 is obvious under § 103 based on Helf and U.S. Patent No.
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`5,459,683 to Uesugi (“Uesugi”) (Ex. 1015).
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`(viii) Claims 44-45 are obvious under § 103 based on Helf, Martin, and
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`Uesugi.
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`Fee for Inter Partes Review (§ 42.15(a))
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`C.
`The Director is authorized to charge the fee specified by 37 CFR § 42.15(a)
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`to Deposit Account No. 50-1597.
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`III. The ’345 Patent and Background Technology
`The ’345 patent describes a noise suppression scheme that uses the well-
`
`known spectral subtraction process described in Boll. See Ex. 1001, 1:58-2:1
`
`(citing Ex. 1009 (Boll)). Most of the specification is directed to describing
`
`conventional features of the spectral subtraction technique or conventional digital
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`signal processing steps, such as using a Fourier transform to convert the signal
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`between the time domain and the frequency domain. E.g., Ex. 1001, 1:58-2:44,
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`4:50-5:34, Fig. 1. A brief background of audio signal processing and Boll follows.
`
`A. Background Technologies
`1.
`Audio Signal Processing
`A standard graphical depiction of sound, shown below, is as a sinusoidal
`
`wave where its amplitude corresponds to how loud it is and its frequency
`
`corresponds to its pitch. Ex. 1004, ¶¶39-42.
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`Ex. 1004, ¶43. The graphs above are in the “time domain”: they depict time on the
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`x-axis, and signal amplitude on the y-axis. Id., ¶40. The left graph is an analog
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`signal; the right graph is a digital version of the same signal, and each blue dot is
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`referred to as a “sample” or a “point.” Id., ¶43.
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`Many sounds (e.g., music or human speech) are comprised of a combination
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`of several different frequencies (e.g., a musical chord is several notes played at the
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`same time). Id., ¶44. A graph of a sound containing multiple frequencies looks
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`like a single signal (see middle graph below).
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`
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`Ex. 1012, 123, 135; Ex. 1004, ¶51. Simply inspecting the time domain
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`representation of the signal (middle) does not reveal which frequencies are present.
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`However, the “Fourier transform” (e.g., an “FFT”) can be used to separate the
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`signal into its individual frequency components. Ex. 1004, ¶¶45-46, 50. The result
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`is a “frequency domain” representation of the signal (right). Id., ¶46. In the top
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`graph of the figure above, the primary frequency components are 900 Hz, 2.5 kHz,
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`and 3.5 kHz, while the bottom graph shows only a 1 kHz signal. Id., ¶51.
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`In the frequency domain, a graph of a digital audio signal typically is
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`depicted as a histogram. Id., ¶46. The signal is divided into “frequency bins”
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`where each bin corresponds to one of the frequencies present in the signal. Id.,
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`¶46. The value of each frequency bin is a “complex number,” which is a pair of
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`numbers that reflect properties of the signal at that frequency, including its
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`magnitude and phase. Id., ¶¶47-49. In the graph below, magnitude is depicted.
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`
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`Processing the audio signal in the frequency domain allows certain
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`operations to be more easily performed on each frequency individually. Ex. 1004,
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`¶¶54-55. However, the signal must be converted back to the time domain using an
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`inverse Fourier transform (e.g., an IFFT) before the signal can be used to recreate
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`the sound. Id., ¶56.
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`Dr. Hochwald provides a more detailed explanation of these basic principles
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`and techniques of digital signal processing at ¶¶39-57 of his declaration (Ex.
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`1004). His explanation is provided as an aid to the Board, but since those basic
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`principles would be well known to a skilled person, they are not necessary to
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`support the specific reasons why the claims are unpatentable in this proceeding.
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`Spectral Subtraction and Boll
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`2.
`Spectral subtraction is a process for removing background noise in an audio
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`signal (e.g., the sound of a fan) that works by subtracting the noise out of the signal
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`on a frequency by frequency (i.e., spectral) basis. Ex. 1004, ¶58.
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`The conventional implementation of this technique is described in Boll. In
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`it, a window function is first applied to the time-domain audio signal to divide it
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`into a series of overlapping frames (e.g., into groups of 256 samples which might
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`represent 50 µs of sound), and then each frame is converted to the frequency
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`domain using an FFT. Ex. 1009, 116; Ex. 1004, ¶¶68-71.
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`Next, an algorithm estimates the level of background noise in each
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`frequency bin. Ex. 1009, 114. Boll calculates the noise estimate in the signal by
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`averaging over time the values of each bin during periods where there is no speech.
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`Ex. 1009, 114, 116. To distinguish between speech and non-speech activity Boll
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`uses a voice switch that detects whether each audio frame as a whole contains
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`speech. Id., 116. After the noise spectrum is estimated, it is removed from each
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`frequency in the audio signal by subtracting the noise value (shown in gold) from
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`the corresponding frequency bin of the signal (shown in blue). Ex. 1004, ¶¶60-63,
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`72-74. The result is a cleaner signal with some of the noise removed. Id., ¶62.
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`Boll performs the subtraction step using a filter, which multiples the signal
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`magnitude by a filter value (e.g., by 0.8, which subtracts 20% from the signal). Ex.
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`1009, 116.
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`
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`Finally, after the noise has been removed, the signal can be converted back
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`into the time domain using an IFFT. Ex. 1009, 117. Boll explains that before
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`converting the signal back to the time domain, additional operations can be
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`performed on the signal to further reduce the noise. Id. For example, Boll
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`describes two residual noise reduction processes that can further attenuate any
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`noise remaining. Id. Boll also describes a magnitude averaging process that can
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`be used to smooth the signal estimates over time. Id., 114.
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`The ’345 Patent Disclosure
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`B.
`The noise suppression scheme in the ’345 patent similarly starts by dividing
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`an audio signal into frames and converting via FFT each frame from the time
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`domain to the frequency domain. Ex. 1001, 4:65-5:14. A noise processing step
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`then estimates the noise level in each frequency bin, and subtracts it from the
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`signal. Id., 5:58-65. The signal is then converted back to the time domain. This
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`process is generally illustrated in Figure 1 (below).
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`
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`The noise estimate for each bin is calculated by averaging over time the bin
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`values that contain only noise. Id., 6:50-55. The ’345 patent describes an
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`“exponential” averaging process that calculates the average as 0.95 times the
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`previous estimate plus 0.05 time the new noise value:
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`N(n) = 0.05*Y(n) + 0.95*N(n).
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`Id., 6:53-55, Fig. 3.
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`To determine whether a bin contains speech or only noise, the bin’s
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`magnitude is compared to an adaptive threshold (308). Id., 6:10-19, 6:46-57. If
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`the magnitude is less than the threshold, it is considered to be noise and is used by
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`an exponential averaging unit (310) to calculate the noise estimate (312) for the
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`frequency bin. Id., 6:46-55. If it is greater than the threshold, it is identified as
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`speech and the noise estimate is not updated. Id. This process is illustrated in
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`Figure 3 (below).
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`
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`The ’345 patent states that its use of a threshold detector for each frequency bin
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`eliminates the need for a “voice switch” that detects non-speech or noise-only
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`frames. Id., 1:58-64, 2:45-47, 3:24-31.
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`The noise estimate is then used in the subtracting step to remove the noise
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`from the signal. Id., 6:58-61. The ’345 patent admits that noise can be removed
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`from a signal using any of a number of different, but well-known mathematical
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`operations, including simple subtraction, a filter multiplication, and a Wiener filter
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`function. Id., 3:60-67. After the noise values have been subtracted, the signal is
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`converted back to the time domain using an inverse FFT. Id., 9:1-5.
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`The ’345 patent also describes a specific algorithm for setting the threshold
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`in each frequency bin. Id., 9:54-10:18, 12:24-39 (claims 4-11, 39-41). In one
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`embodiment, this threshold is calculated by tracking the minimum value of the bin
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`over a five second period, and multiplying the minimum observed value by a factor
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`of 4. Id., 6:46-48. The bin’s minimum value is tracked using two values: a “future
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`minimum” (304), which tracks the minimum observed value during the current
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`five second period, and a “current minimum” (306) that is used to calculate the
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`noise threshold and reflects the minimum value observed during the previous five
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`second period. Id., 6:10-41, Fig. 3.
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`Other dependent claims concern additional features of the noise reduction
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`scheme (e.g., mathematical shortcuts that can be used to derive the magnitude of
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`each frequency bin using the output of the FFT operation, which is a complex
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`number that includes a real and imaginary part (id., 3:46-51, 6:61-7:17),
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`“smoothing,” i.e., averaging, various components of the signal by calculating an
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`average over time or over neighboring frequencies (id., 3:21-23, 3:51-57), and
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`residual noise reduction to reduce noise in the signal after spectral subtraction has
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`been performed (id., 4:5-11)).
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`C. Effective Filing Date
`The ’345 patent does not claim priority to another application. Accordingly,
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`the effective filing date of the ’345 patent claims is February 18, 1999.
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`Person of Ordinary Skill in the Art
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`D.
`A person of ordinary skill in the art in February 1999 would have been a
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`person with a good working knowledge of digital signal processing techniques and
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`their applications. That person would have gained this knowledge through an
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`undergraduate education in electrical engineering or a comparable field, in
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`combination with either a graduate degree (or two years of graduate work) in
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`electrical engineering or a comparable field, or through two years of practical work
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`experience, where such graduate education or work experience focused on or
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`involved the use of digital signal processing techniques. Ex. 1004, ¶37.
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`Petitioner’s positions regarding how a person of ordinary skill would have
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`understood the ’345 patent claims and the teachings of the prior art references are
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`supported by the testimony of Bertrand Hochwald, Ph. D., an expert in digital
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`signal processing who has over 20 years of experience in the field. Id., ¶¶1-11.
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`IV. Claim Construction
`Claims must be given their broadest reasonable construction in light of the
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`specification. 37 CFR § 42.100(b); Cuozzo Speed Techs., LLC v. Lee, 136 S. Ct.
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`2131 (2016). In this proceeding, the teachings of the asserted prior art references
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`are squarely within the scope of the challenged claims, and consequently, the
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`Board likely will not need to adopt specific constructions. See Vivid Techs., Inc. v.
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`Am. Sci. & Eng’g, Inc., 200 F.3d 795, 803 (Fed. Cir. 1999) (claim terms need only
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`be construed to the extent necessary to resolve the case).
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`In anticipation of constructions Patent Owner may advance, Petitioner sets
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`forth proposed constructions for certain terms below. Petitioner reserves its right
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`to advance different constructions in district court or ITC litigation based on a
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`different claim construction standard, and to establish the claims are invalid under
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`35 U.S.C. § 112 in such proceedings.
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`A.
`“magnitude”
`Claims 1 and 38 each specify detecting whether a “magnitude” of each
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`frequency bin is less than that bin’s threshold. The specification explains that the
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`magnitude of the frequency bin can correspond to its actual magnitude or to a
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`value that approximates its magnitude. Ex. 1001, 2:11-19, 2:24-30, 5:40-41 (“the
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`signal magnitude (Y) is estimated… using an approximation formula”), 5:34-44.
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`The specification does not require use of any particular technique for measuring or
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`estimating the magnitude of a frequency bin. Ex. 1004, ¶¶94-95. Accordingly, the
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`broadest reasonable interpretation of the term “magnitude” includes both the
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`signal’s actual magnitude as well as an approximation of its magnitude. Ex. 1001,
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`2:11-19, 2:24-30, 5:34-44.
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`During previous litigation, Patent Owner contended the term “magnitude”
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`was “a measure of the level of the signal in a frequency bin” calculated as “a
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`function of the square[s]” or “absolute value[s]” of the “frequency domain
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`component[s] of the frequency bin.” Ex. 1019, 21. Patent Owner’s position is thus
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`consistent with, but broader than, Petitioner’s proposed construction here.
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`B.
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`“frequency spectrum generator” / “generating the frequency
`spectrum”
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`Claim 1 recites a “frequency spectrum generator” while claim 38 recites
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`“generating the frequency spectrum.” No requirements of these elements are
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`recited in the claims. The ’345 patent shows these functions being performed by
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`hardware or software that converts the audio signal from the time domain into the
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`frequency domain, such as by a fast Fourier transform (FFT) operation. Ex. 1001,
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`2:11-14, 5:10-21. The broadest reasonable interpretation of these terms thus
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`includes hardware or software that converts an audio signal from the time domain
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`into the frequency domain. Ex. 1004, ¶96.
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`C.
`“threshold detector for setting a threshold… and for detecting”
`Claim 1 recites a “threshold detector for setting a threshold… and for
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`detecting… whether the magnitude… is less than the corresponding threshold.”
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`The term needs no construction because its meaning is clear from the claim
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`language, which specifies the functions that the “threshold detector” performs.
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`That functionality would include hardware or software that, for each frequency bin,
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`sets a threshold and determines whether the magnitude of the frequency bin is less
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`than that threshold. Ex. 1001, 3:30-36, 6:46-57; Ex. 1004, ¶97.
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`Patent Owner may contend this term should be construed as a means-plus-
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`function element because it is structured as an element for performing a function:
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`“setting a