UNITED STATES PATENT AND TRADEMARK OFFICE
`
`_________________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`_________________
`
`APPLE INC.,
`Petitioner
`
`v.
`
`ZENTIAN LIMITED,
`Patent Owner
`_________________
`
`Inter Partes Review Case No. IPR2023-00033
`U.S. Patent No. 7,587,319
`
`DECLARATION OF CHRISTOPHER SCHMANDT
`IN SUPPORT OF PETITION FOR INTER PARTES REVIEW OF
`U.S. PATENT NO. 7,587,319
`
`Amazon / Zentian Limited
`Exhibit 1003
`Page 1
`
`

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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`
`TABLE OF CONTENTS
`
`I.
`
`INTRODUCTION AND QUALIFICATIONS ........................................ 10
`A.
`EDUCATIONAL BACKGROUND AND PROFESSIONAL EXPERIENCE ......... 10
`II. METHODOLOGY; MATERIALS CONSIDERED ............................... 13
`III. OVERVIEW AND LEGAL STANDARDS ............................................. 15
`A.
`PERSON OF ORDINARY SKILL IN THE ART ............................................ 16
`B.
`OBVIOUSNESS ...................................................................................... 17
`C.
`ANALOGOUS ART ................................................................................ 22
`D.
`CLAIM CONSTRUCTION ....................................................................... 23
`IV. LEVEL OF A PERSON OF ORDINARY SKILL .................................. 23
`V.
`OVERVIEW OF THE TECHNOLOGY ................................................. 24
`A.
`SPEECH RECOGNITION ......................................................................... 24
`B.
`FEATURE VECTORS ............................................................................. 32
`C.
`ACOUSTIC MODELS ............................................................................. 36
`D.
`HIDDEN MARKOV MODELS ................................................................. 37
`E.
`PRIOR ART SPEECH RECOGNITION SYSTEMS ....................................... 45
`VI. OVERVIEW OF THE ’319 PATENT ...................................................... 49
`VII. OVERVIEW OF THE PRIOR ART ........................................................ 50
`A.
`OVERVIEW OF THELEN ......................................................................... 50
`B.
`OVERVIEW OF BAILEY .......................................................................... 51
`C.
`OVERVIEW OF CHEN ............................................................................ 52
`D.
`OVERVIEW OF HUANG ......................................................................... 52
`E.
`OVERVIEW OF JIANG ............................................................................ 53
`F.
`OVERVIEW OF KATZ ............................................................................. 53
`VIII. OPINIONS REGARDING GROUND 1 ................................................... 54
`A.
`OBVIOUSNESS OF MODIFYING ELECTRONIC HARDWARE AND
`SOFTWARE TO BE CIRCUITRY .............................................................. 54
`CLAIMS 46, 50, 54, 64 AND 67 ARE OBVIOUS OVER THELEN IN
`VIEW OF BAILEY IN FURTHER VIEW OF CHEN ....................................... 55
`1.
`Claim 46 ................................................................................... 55
`a)
`Claim 46(Pre): “A speech recognition circuit
`comprising” ................................................................... 55
`Claim 46(a): “an input buffer receiving processed
`speech parameters;” ....................................................... 55
`
`B.
`
`b)
`
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`c)
`
`e)
`
`f)
`
`g)
`
`d)
`
`Declaration of Chris Schmandt
`Patent No. 7,587,319
`Claim 46(b): “a plurality of lexical memories
`containing in combination complete lexical data
`for word recognition, each lexical memory
`containing part of said complete lexical data;” ............. 63
`Claim 46(c): “a plurality of processors connected
`in parallel to said input buffer for processing the
`speech parameters in parallel,” ...................................... 70
`Claim 46(d): “said processors being arranged in
`groups of processors, each group of processors
`being connected to a lexical memory;” ......................... 72
`Claim 46(e): “a control processor controlling each
`processor to process said speech parameters using
`partial lexical data read from a respective said
`lexical memory; and” ..................................................... 78
`Claim 46(f): “a results memory storing the results
`of the processing of the speech parameters from
`said processors.” ............................................................ 82
`Claim 50 ................................................................................... 86
`a)
`Claim 50: “A speech recognition circuit according
`to claim 46, wherein each processor compares the
`processed speech parameters with the lexical data
`in a corresponding lexical memory to identify
`words as a word recognition event and sends
`information identifying the identified words to said
`results memory as the processing results.” .................... 86
`Claim 67 ................................................................................... 88
`a)
`Claim 67: “A speech recognition circuit according
`to claim 46, wherein said lexical memories store
`said lexical data as Hidden Markov Models, and
`each processor performs the Viterbi search
`algorithm using a respective part of said lexical
`data.” .............................................................................. 88
`IX. OPINIONS REGARDING GROUND 2 ................................................... 90
`A.
`CLAIMS 47-49 ARE OBVIOUS OVER THELEN IN VIEW OF BAILEY
`AND CHEN IN FURTHER VIEW OF HUANG ........................................... 90
`1.
`Claim 47 ................................................................................... 90
`a)
`Claim 47: “A speech recognition circuit according
`to claim 46, wherein each lexical memory stores
`lexical data as at least one lexical tree data
`
`2.
`
`3.
`
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`Exhibit 1003
`Page 3
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`

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`2.
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`3.
`
`Declaration of Chris Schmandt
`Patent No. 7,587,319
`structure, each lexical tree data structure comprises
`a model of words having common prefix
`components, and an initial component of each
`lexical tree data structure is unique.” ............................. 90
`Claim 48 ................................................................................... 95
`a)
`Claim 48: “A speech recognition circuit according
`to claim 47, wherein each lexical memory stores
`said lexical tree data structure as an n phone model
`of words, where n is an integer, and said
`components comprise n phones.” .................................. 95
`Claim 49 ................................................................................... 97
`a)
`Claim 49: “A speech recognition circuit according
`to claim 48, wherein each lexical memory stores
`said lexical tree data structure as a mono phone
`model of words, and said lexical tree processors
`use said mono phone models to generate context
`dependant phone models of words dynamically for
`use in processing the speech parameters.” ..................... 97
`OPINIONS REGARDING GROUND 3 ................................................. 101
`A.
`CLAIMS 53 AND 58-59 ARE OBVIOUS OVER THELEN IN VIEW OF
`BAILEY AND CHEN IN FURTHER VIEW OF JIANG ................................ 101
`1.
`Dependent Claim 53 .............................................................. 101
`a)
`Claim 53: “A speech recognition circuit according
`to claim 46, wherein each processor determines
`and outputs scores for words in the processing
`results at word recognition events.” ............................ 101
`Dependent Claim 58 .............................................................. 103
`a)
`Claim 58: “A speech recognition circuit according
`to claim 46, wherein said processors determine and
`output scores in the processing results during the
`processing of said speech parameters.” ....................... 103
`XI. OPINIONS REGARDING GROUND 4 ................................................. 105
`A.
`CLAIMS 51 IS OBVIOUS OVER THELEN IN VIEW OF BAILEY AND
`CHEN IN FURTHER VIEW OF KATZ ..................................................... 105
`1.
`Dependent Claim 51 .............................................................. 105
`a)
`Claim 51: “A speech recognition circuit according
`to claim 50, a including language model processor
`providing a language model output for modifying
`
`X.
`
`2.
`
`Amazon / Zentian Limited
`Exhibit 1003
`Page 4
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`

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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`the processing results at a word recognition event
`by a said processor.” .................................................... 105
`XII. CONCLUSION ......................................................................................... 108
`
`Amazon / Zentian Limited
`Exhibit 1003
`Page 5
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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`
`CLAIM LISTING
`
`CLAIM 46:
`
`Claim 46[Pre] A speech recognition circuit comprising:
`
`46(a) an input buffer receiving processed speech parameters;
`
`46(b) a plurality of lexical memories containing in combination complete
`
`lexical data for word recognition, each lexical memory containing part of said
`
`complete lexical data;
`
`46(c) a plurality of processors connected in parallel to said input buffer for
`
`processing the speech parameters in parallel, said processors being arranged in
`
`groups of processors, each group of processors being connected to a lexical
`
`memory;
`
`46(d) a control processor controlling each processor to process said speech
`
`parameters using partial lexical data read from a respective said lexical memory;
`
`and
`
`46(e) a results memory storing the results of the processing of the speech
`
`parameters from said processors.
`
`Claim 47:
`
`A speech recognition circuit according to claim 46, wherein each lexical
`
`memory stores lexical data as at least one lexical tree data structure, each lexical
`
`Amazon / Zentian Limited
`Exhibit 1003
`Page 6
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`

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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`tree data structure comprises a model of words having common prefix components,
`
`and an initial component of each lexical tree data structure is unique.
`
`Claim 48:
`
`A speech recognition circuit according to claim 47, wherein each lexical
`
`memory stores said lexical tree data structure as an n phone model of words, where
`
`n is an integer, and said components comprise n phones.
`
`Claim 49:
`
`A speech recognition circuit according to claim 48, wherein each lexical
`
`memory stores said lexical tree data structure as a mono phone model of words,
`
`and said lexical tree processors use said mono phone models to generate context
`
`dependant phone models of words dynamically for use in processing the speech
`
`parameters.
`
`Claim 50:
`
`A speech recognition circuit according to claim 46, wherein each processor
`
`compares the processed speech parameters with the lexical data in a corresponding
`
`lexical memory to identify words as a word recognition event and sends
`
`information identifying the identified words to said results memory as the
`
`processing results.
`
`Amazon / Zentian Limited
`Exhibit 1003
`Page 7
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`

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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`
`Claim 51:
`
`A speech recognition circuit according to claim 50, a including language
`
`model processor providing a language model output for modifying the processing
`
`results at a word recognition event by a said processor.
`
`Claim 53:
`
`A speech recognition circuit according to claim 51, wherein each processor
`
`determines and outputs scores for words in the processing results at word
`
`recognition events.
`
`Claim 54:
`
`A speech recognition circuit according to claim 46, wherein said processors
`
`process said speech parameters by comparing said speech parameters with said
`
`lexical data or data derived from lexical data in respective said lexical memories.
`
`Claim 58:
`
`A speech recognition circuit according to claim 46, wherein said processors
`
`determine and output scores in the processing results during the processing of said
`
`speech parameters.
`
`Claim 59:
`
`A speech recognition circuit according to claim 58, wherein said processors
`
`prune the processing of the speech parameters in dependence upon the determined
`
`scores.
`
`Amazon / Zentian Limited
`Exhibit 1003
`Page 8
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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`
`Claim 64:
`
`A speech recognition circuit according to claim 46, wherein said input buffer
`
`is arranged to receive said speech parameters as feature vectors.
`
`Claim 67:
`
`A speech recognition circuit according to claim 46, wherein said lexical
`
`memories store said lexical data as Hidden Markov Models, and each processor
`
`performs the Viterbi search algorithm using a respective part of said lexical data.
`
`
`
`Amazon / Zentian Limited
`Exhibit 1003
`Page 9
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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`
`I, Christopher Schmandt, declare as follows:
`
`I.
`
`INTRODUCTION AND QUALIFICATIONS
`1.
`I am over the age of 21 and am competent to make this declaration.
`
`A. Educational Background and Professional Experience
`2.
`I retired several years ago after a 40-year career at the Massachusetts
`
`Institute of Technology (“MIT”); for most of that time I was employed as a Principal
`
`Research Scientist at the Media Laboratory. In that role I also served as faculty for
`
`the MIT Media Arts and Sciences academic program. I was a founder of the Media
`
`Laboratory, a research lab which now spans two buildings.
`
`3.
`
`I received my B.S. degree in Electrical Engineering and Computer
`
`Science from MIT in 1978, and my M.S. in Visual Studies (Computer Graphics) also
`
`from MIT. I was employed at MIT since 1980, initially at the Architecture Machine
`
`Group which was an early computer graphics and interactive systems research lab.
`
`In 1985, I helped found the Media Laboratory and continued to work there until
`
`retirement. I was director of a research group titled “Living Mobile.” My research
`
`spanned distributed communication and collaborative systems, with an emphasis on
`
`multi-media and user interfaces, with a strong focus on speech-based systems. I have
`
`over 70 published conference and journal papers and one book in the field of speech
`
`technology and user interaction.
`
`Amazon / Zentian Limited
`Exhibit 1003
`Page 10
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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`For the first fifteen years of my career, my research emphasized speech
`
`4.
`
`recognition and speech user interfaces. I built the first conversational computer
`
`system utilizing speech recognition and synthesis (“Put That There”) starting in
`
`1980. I continued to innovate speech user interfaces using recognition, text-to-
`
`speech synthesis, and recorded audio in a wide variety of projects. I built one of the
`
`first graphical user interfaces for audio editing, employing keyword recognition on
`
`voice memos in 1982 (Intelligent Ear). I built the first research-grade unified
`
`messaging system, which combined text and voice messages into a single inbox,
`
`with speech recognition over the phone for remote access, and a graphical user
`
`interface for desktop access in 1983 (Phone Slave). Along with my students we built
`
`the first system for real time spoken driving directions, including speech-accessible
`
`maps of Cambridge, Massachusetts in 1987 (Back Seat Driver). We built some of
`
`the earliest speech-based personal assistants for managing messages, calendar,
`
`contacts, etc. (Conversational Desktop 1985, Chatter 1993, MailCall 1996). We built
`
`quite a few systems employing speech recognition in handheld mobile devices
`
`(ComMotion 1999, Nomadic Radio 2000, Impromptu 2001, and Symphony 2004,
`
`for example). We applied speech recognition to large bodies of everyday
`
`conversations captured with a wearable device and utilized as a memory aid
`
`(Memory Prosthesis 2004). We used speech recognition on radio newscasts to build
`
`a personalized version of audio newscasts (Synthetic News Radio, 1999) and also
`
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`Exhibit 1003
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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`investigated adding speech recognition to a mouse-based window system a few years
`
`earlier.
`
`5.
`
`I was later awarded the prestigious Association for Computing
`
`Machinery (ACM) Computer Human Interface (CHI) Academy membership
`
`specifically for those years of work pioneering speech user interfaces.
`
`6.
`
`In the course of my research, I built a number of speech recognition
`
`client/server distributed systems, with the first being in 1985. Much of the initial
`
`motivation for a server architecture was that speech recognition required expensive
`
`digital signal processing hardware that we could not afford to put on each computer,
`
`so a central server with the required hardware was used. Later versions of the speech
`
`recognition server architecture allowed certain computers to perform specialized
`
`tasks serving a number of client computers providing voice user interfaces, either on
`
`screens or over telephone connections.
`
`7.
`
`Because of my early work with distributed speech systems, I served for
`
`several years in the mid-1990s with a working group on the impact of multimedia
`
`systems on the Internet reporting to the Internet Engineering Task Force (IETF) and
`
`later the Internet Activities Board (IAB). This work impacted emerging standards
`
`such as Session Initiation Protocol (SIP).
`
`In my faculty position I taught graduate level courses in speech technology and user
`
`interaction design, and directly supervised student research and theses at the
`
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`Exhibit 1003
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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`Bachelors, Masters, and PhD level. I oversaw the Masters and PhD thesis programs
`
`for the entire Media Arts and Sciences academic program during my more senior
`
`years. I also served on the Media Laboratory intellectual property committee for
`
`many years.
`
`II. METHODOLOGY; MATERIALS CONSIDERED
`8.
`I have relied upon my education, knowledge, and experience with
`
`speech recognition systems more generally, as well as the other materials as
`
`discussed in this declaration in forming my opinions.
`
`9.
`
`For this work, I have been asked to review U.S. Patent No. 7,587,319
`
`(“’319 Patent”) (Ex. 1001) including the specification and claims, and the ’319
`
`Patent’s prosecution history (“’319 File History”) (Ex. 1002). In developing my
`
`opinions relating to the ’319 Patent, I have considered the materials cited or
`
`discussed herein, including those itemized in the Exhibit Table below.
`
`Description
`Exhibit
`Exhibit 1001 U.S. Patent No. 7,587,319 (“’319 Patent”)
`Exhibit 1002 Prosecution History for the 7,587,319 Patent (“’319 File History”)
`Exhibit 1004 U.S. Patent No. 6,374,219 to Jiang (“Jiang”)
`Exhibit 1005 U.S. Patent No. 5,428,803 to Chen et al. (“Chen”)
`Exhibit 1006 Hsiao-Wuen Hon, A survey of hardware architectures designed for
`speech recognition, Carnegie Mellon University, 1991 (“Hon”)
`Exhibit 1007 Ph.D. Thesis of Mosur Ravishankar (“Ravishankar”)
`Exhibit 1008
`Intentionally Left Blank
`Exhibit 1009 U.S. Patent No. 5,983,180 to Robinson (“Robinson”)
`Exhibit 1010 U.S. Patent No. 5,036,539 to Wrench Jr., et al. (“Wrench”)
`Exhibit 1011 Frederick Jelinek, Statistical Methods for Speech Recognition, The
`MIT Press, 1997 (“Jelinek”)
`
`Amazon / Zentian Limited
`Exhibit 1003
`Page 13
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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`Exhibit 1012 Christopher Schmandt, Voice Communication with Computers,
`Van Nostrand Reinhold, 1994 (“Schmandt”)
`Exhibit 1013 Lawrence Rabiner and Biing-Hwang Juang, Fundamentals of
`Speech Recognition Prentice Hall PTR, 1993 (“Rabiner”)
`Exhibit 1014 Richard Klevans and Robert Rodman, Voice Recognition, Artech
`House, 1997 (“Klevans”)
`Exhibit 1015 U.S. Patent No. 7,120,582 to Young et al. (“Young”)
`Exhibit 1016 John Holmes and Wendy Holmes, Speech Synthesis and
`Recognition, 2nd Edition, Taylor & Francis, 2001 (“Holmes”)
`Exhibit 1017 U.S. Patent No. 4,926,488 to Nadas et al. (“Nadas”)
`Exhibit 1018 U.S. Patent No. 6,182,037 to Maes (“Maes”)
`Exhibit 1019 U.S. Patent Application Publication No. 2003/0220796 to Aoyama
`et al. (“Aoyama”)
`Exhibit 1020 U.S. Patent No. 6,092,045 to Stubley et al. (“Stubley”)
`Exhibit 1021 U.S. Patent No. 6,151,574 to Lee et al. (“Lee”)
`Exhibit 1022 U.S. Patent No. 6,580,814 to Ittycheriah et al. (“Ittycheriah”)
`Exhibit 1023 U.S. Patent No. 6,452,348 to Toyoda (“Toyoda”)
`Exhibit 1024 William A. Wulf and C.G. Bell, C.mmp–A multi-mini-processor,
`Carnegie-Mellon University, 1972 (“Wulf”)
`Exhibit 1025 Lee D. Erman, Richard D. Fennell, Victor R. Lesser, and D. Raj
`Reddy, System Organizations
`for Speech Understanding:
`Implications of Network and Multiprocessor Computer
`Architectures for AI, IEEE Transactions on Computers, Vol. C-25,
`No. 4, April 1976 (“Erman”)
`Exhibit 1026 U.S. Patent No. 6,393,481 to Deo et al. (“Deo”)
`Exhibit 1027 U.S. Patent No. 6,615,338 to Tremblay et al. (“Tremblay”)
`Exhibit 1028 U.S. Patent No. 5,922,076 to Garde (“Garde”)
`Exhibit 1029 Lawrence R. Rabiner, A Tutorial on Hidden Markov Models and
`Selected Applications in Speech Recognition, Proceedings of the
`IEEE, Vol. 77, No. 2, February 1989 (“Rabiner 89”)
`Exhibit 1030 U.S. Patent No. 6,526,380 to Thelen et al. (“Thelen”)
`Exhibit 1031 U.S. Patent No. 5,459,798 to Bailey et al. (“Bailey”)
`Exhibit 1033 Declaration of June Ann Munford (“Munford”)
`Exhibit 1034 U.S. Patent No. 6,076,056 to Huang et al. (“Huang”)
`Exhibit 1035 U.S. Patent No. 4,831,550 to Katz (“Katz”)
`Exhibit 1036 U.S. Patent No. 4,567,606 to Vensko et al. (“Vensko”)
`Exhibit 1037 U.S. Patent No. 4,907,278 to Cecinati et al. (“Cecinati”)
`
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`Exhibit 1003
`Page 14
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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`Exhibit 1038 B. I. (Raj) Pawate and Peter D. Robinson, “Implementation of an
`HMM-Based, Speaker-Independent Speech Recognition System on
`the TMS320C2x and TMS320C5x”, 1996 (“Pawate”)
`Exhibit 1039 U.S. Patent No. 4,386,416 to Giltner et al. (“Giltner”)
`Exhibit 1040 U.S. Patent No. 4,571,700 to Emry, Jr. et al. (“Emry”)
`Exhibit 1041 U.S. Patent No. 4,646,261 to Ng (“Ng”)
`Exhibit 1042 U.S. Patent No. 5,150,399 to Yasuda (“Yasuda”)
`
`
`10.
`
`I have considered these materials from the viewpoint of a POSITA as
`
`of the priority date of the ’319 Patent. For the purposes of this declaration, I have
`
`been asked to assume that the priority date of the ’319 Patent is February 4, 2002. I
`
`note that my opinions provided in this Declaration are made from the perspective of
`
`a POSITA as of this priority date of the ’319 Patent, unless expressly stated
`
`otherwise. To the extent that I use any verb tense in this Declaration that is present
`
`tense (e.g., “a POSITA would understand” instead of “a POSITA would have
`
`understood”), such verb tense should be understood to be my opinion as of the ’319
`
`Patent’s priority date (again, unless expressly stated otherwise). I merely use the
`
`present verb tense for ease of reading.
`
`III. OVERVIEW AND LEGAL STANDARDS
`11.
`In formulating my opinions, I have been instructed to apply certain
`
`legal standards. I am not a lawyer. I do not expect to offer any testimony regarding
`
`what the law is. Instead, the following sections summarize the law as I have been
`
`instructed to apply it in formulating and rendering my opinions found later in this
`
`declaration. I understand that, in an inter partes review (“IPR”) proceeding, patent
`
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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`claims may be deemed unpatentable if it is shown that they were anticipated or
`
`rendered obvious in view of the prior art. I understand that prior art in an IPR review
`
`is limited to patents or printed publications that predate the priority date of the patent
`
`at issue. I understand that questions of claim clarity (definiteness) and enablement
`
`cannot be considered as a ground for considering the patentability of a claim in these
`
`proceedings.
`
`A.
`12.
`
`Person of Ordinary Skill in the Art
`I understand that the ’319 Patent, the record of proceedings at the Patent
`
`Office (which I understand is called the “File History” or “Prosecution History”),
`
`and the teachings of the prior art are evaluated from the perspective of a person of
`
`ordinary skill in the art (“POSITA”). I understand that the factors considered in
`
`determining the ordinary level of skill in the art include: (i) the levels of education
`
`and experience of persons working in the field; (ii) the types of problems
`
`encountered in the field; and (iii) the sophistication of the technology. I may also
`
`consider, if available, the education level of the inventor, prior art solutions to the
`
`problems encountered in the art, and the rapidity with which innovations are made
`
`in the relevant art.
`
`13.
`
`I understand that a person of ordinary skill in the art is not a specific
`
`real individual, but rather a hypothetical individual having the qualities reflected by
`
`the factors above. This hypothetical person has knowledge of all prior art in the
`
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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`relevant field as if it were arranged on a workshop wall and takes from each reference
`
`what it would teach to a person having the skills of a POSITA.
`
`B.
`14.
`
`Obviousness
`I understand that a claim may be invalid under § 103(a) if the subject
`
`matter described by the claim as a whole would have been “obvious” to a
`
`hypothetical POSITA in view of a single prior art reference or in view of a
`
`combination of references at the time the claimed invention was made. Therefore, I
`
`understand that obviousness is determined from the perspective of a hypothetical
`
`POSITA. I further understand that a hypothetical POSITA is assumed to know and
`
`to have all relevant prior art in the field of endeavor covered by the patent in suit and
`
`all analogous prior art. I understand that obviousness in an IPR review proceeding
`
`is evaluated using a preponderance of the evidence standard, which means that the
`
`claims must be more likely obvious than nonobvious.
`
`15.
`
`I also understand that an analysis of whether a claimed invention would
`
`have been obvious should be considered in light of the scope and content of the prior
`
`art, the differences (if any) between the prior art and the claimed invention, and the
`
`level of ordinary skill in the pertinent art involved. I understand as well that a prior
`
`art reference should be viewed as a whole. I understand that in considering whether
`
`an invention for a claimed combination would have been obvious, I may assess
`
`whether there are apparent reasons to combine known elements in the prior art in the
`
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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`manner claimed in view of interrelated teachings of multiple prior art references, the
`
`effects of demands known to the design community or present in the marketplace,
`
`and/or the background knowledge possessed by a POSITA. I also understand that
`
`other principles may be relied on in evaluating whether a claimed invention would
`
`have been obvious, and that these principles include the following:
`
`• A combination of familiar elements according to known methods is
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`likely to be obvious when it does no more than yield predictable results;
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`• When a device or technology is available in one field of endeavor,
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`design incentives and other market forces can prompt variations of it,
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`either in the same field or in a different one, so that if a POSITA can
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`implement a predictable variation, the variation is likely obvious;
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`• If a technique has been used to improve one device, and a POSITA
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`would have recognized that it would improve similar devices in the
`
`same way, using the technique is obvious unless its actual application
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`is beyond his or her skill;
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`• An explicit or implicit teaching, suggestion, or motivation to combine
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`two prior art references to form the claimed combination may
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`demonstrate obviousness, but proof of obviousness does not depend on
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`or require showing a teaching, suggestion, or motivation to combine;
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`Amazon / Zentian Limited
`Exhibit 1003
`Page 18
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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`• Market demand, rather than scientific literature, can drive design trends
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`and may show obviousness;
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`• In determining whether the subject matter of a patent claim would have
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`been obvious, neither the particular motivation nor the avowed purpose
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`of the named inventor controls;
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`• One of the ways in which a patent’s subject can be proved obvious is
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`by noting that there existed at the time of invention a known problem
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`for which there was an obvious solution encompassed by the patent’s
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`claims;
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`• Any need or problem known in the field of endeavor at the time of
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`invention and addressed by the patent can provide a reason for
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`combining the elements in the manner claimed;
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`• “Common sense” teaches that familiar items may have obvious uses
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`beyond their primary purposes, and in many cases a POSITA will be
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`able to fit the teachings of multiple patents together like pieces of a
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`puzzle;
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`• A POSITA is also a person of ordinary creativity, and is not an
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`automaton;
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`• A patent claim can be proved obvious by showing that the claimed
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`combination of elements was “obvious to try,” particularly when there
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`Amazon / Zentian Limited
`Exhibit 1003
`Page 19
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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`is a design need or market pressure to solve a problem and there are a
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`finite number of identified, predictable solutions such that a POSITA
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`would have had good reason to pursue the known options within his or
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`her technical grasp; and
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`• One should not use hindsight in evaluating whether a claimed invention
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`would have been obvious.
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`16.
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`I also understand that an obviousness determination includes the
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`consideration of various factors such as: (1) the scope and content of the prior art,
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`(2) the differences between the prior art and the asserted claims, (3) the level of
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`ordinary skill in the pertinent art, and (4) the existence of secondary considerations
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`such as commercial success, long-felt but unresolved needs, failure of others, and so
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`forth.
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`17.
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`I am informed that it is improper to combine references where the
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`references teach away from their combination. I am informed that a reference may
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`be said to teach away when a person of ordinary skill in the relevant art, upon reading
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`the reference, would be discouraged from following the path set out in the reference,
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`or would be led in a direction divergent from the path that was taken by the patent
`
`applicant. In general, a reference will teach away if it suggests that the line of
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`development flowing from the reference’s disclosure is unlikely to be productive of
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`the result sought by the patentee. I am informed that a reference teaches away, for
`
`Amazon / Zentian Limited
`Exhibit 1003
`Page 20
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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`example, if (1) the combination would produce a seemingly inoperative device, or
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`(2) the references leave the impression that the product would not have the property
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`sought by the patentee. I also am informed, however, that a reference does not teach
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`away if it merely expresses a general preference for an alternative invention but does
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`not criticize, discredit, or otherwise discourage investigation into the invention
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`claimed.
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`18.
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`I am informed that even if a prima facie case of obviousness is
`
`established, the final determination of obviousness must also consider “secondary
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`considerations” if presented. In most instances, the patentee raises these secondary
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`considerations of non-obviousness. In that context, the patentee argues an invention
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`would not have been obvious in view of these considerations, which include: (a)
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`commercial success of a product due to the merits of the claimed invention; (b) a
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`long-felt, but unsatisfied need for the invention; (c) failure of others to find the
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`solution provided by the claimed invention; (d) deliberate copying of the invention
`
`by others; (e) unexpected results achieved by the invention; (f) praise of the
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`invention by others skilled in the art; (g) lack of independent simultaneous invention
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`within a comparatively short space of time; (h) teaching away from the invention in
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`the prior art.
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`19.
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`I am further informed that secondary considerations evidence is only
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`relevant if the offering party establishes a connection, or nexus, between the
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`Amazon / Zentian Limited
`Exhibit 1003
`Page 21
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`Declaration of Chris Schmandt
`Patent No. 7,587,319
`evid