`
`UNITED STATES PATENT AND TRADEMARK OFFICE
`___________________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`___________________
`
`GOOGLE INC.
`Petitioner
`
`v.
`
`IXI IP, LLC
`Patent Owner
`
`___________________
`
`Case No. IPR2016-01669
`Patent 7,552,124
`___________________
`
`DECLARATION OF LIN CHASE, PH.D., IN SUPPORT OF
`PATENT OWNER’S PRELIMINARY RESPONSE
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`IXI EXHIBIT 2001
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`Case No. IPR2016-01669
`Patent 7,552,124
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`TABLE OF CONTENTS
`
`I.
`
`II.
`
`Introduction ..................................................................................................... 1
`A.
`Engagement .......................................................................................... 1
`B.
`Compensation and Prior Testimony ..................................................... 1
`C. Qualifications and Professional Experience......................................... 1
`D.
`Summary of My Study ......................................................................... 5
`
`Relevant Legal Standards ............................................................................... 6
`A.
`Claim Construction............................................................................... 7
`B. Obviousness .......................................................................................... 7
`
`III. One Of Ordinary Skill In The Art .................................................................. 9
`
`IV. Overview Of The ’124 Patent ....................................................................... 10
`
`V. Opinion On Claim Construction ................................................................... 13
`
`B.
`
`VI. Grounds Based On Maes And Preston ......................................................... 14
`A.
`Summary of the Asserted References ................................................ 15
`1. Maes ......................................................................................... 15
`Preston ..................................................................................... 17
`2.
`Petitioner’s Proposed Combination of Maes and Preston Does
`Not Render Obvious Claims 1 and 6 .................................................. 19
`1. Maes and Preston do not disclose or suggest “parsing the
`high-level code for the keywords” as alleged by
`Petitioner .................................................................................. 19
`2. Maes and Preston do not disclose or suggest
`“determining level of complexity and implementation of
`the high-level code” as alleged by Petitioner........................... 23
`
`VII. Grounds Based On Pazandak, White, And Manson ..................................... 26
`A.
`Summary of the Asserted References ................................................ 26
`Pazandak .................................................................................. 26
`1.
`2. White ........................................................................................ 29
`3. Manson ..................................................................................... 31
`Petitioner’s Proposed Combination of Pazandak, White, and
`Manson Does Not Render Obvious Claims 1 and 6 .......................... 32
`Pazandak, White, and Manson do not disclose or suggest
`1.
`“wherein the high-level code is provided by a user …
`ii
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`
`B.
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`without having to select from menu items …” as alleged
`by Petitioner ............................................................................. 32
`Pazandak, White and Manson do not disclose or suggest
`“parsing the high-level code for the keywords …” as
`alleged by Petitioner ................................................................ 35
`Pazandak, White and Manson do not disclose or suggest
`“determining whether high-level code comprises
`keywords defining one or more relationships and
`conditions corresponding to the operative language” as
`alleged in the Petition ............................................................... 37
`Pazandak, White, and Manson do not disclose or suggest
`“determining level of complexity and implementation of
`the high-level code” as alleged in the Petition ......................... 38
`A person of ordinary skill in the art would not have been
`motivated to modify Pazandak in view of White as
`alleged by Petitioner ................................................................ 41
`
`2.
`
`3.
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`4.
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`5.
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`iii
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`
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`I, Lin Chase, Ph.D., do hereby declare:
`
`I.
`
`INTRODUCTION
`
`A. Engagement
`I have been retained by counsel for Patent Owner as an expert witness
`1.
`
`to render opinions on certain issues concerning Inter Partes Review No. IPR2016-
`
`01669 of U.S. Patent No. 7,552,124 to Vladimir Drukin (hereafter “the ’124
`
`Patent”). This is my written declaration.
`
`B. Compensation and Prior Testimony
`I am being compensated at a standard rate of $375 per hour for my
`2.
`
`study and preparation of this declaration. I am also being reimbursed for
`
`reasonable and customary expenses associated with my work and testimony in this
`
`study. This compensation is not dependent on my opinions or testimony or the
`
`outcome of this matter.
`
`3.
`
`I have previously testified as an expert in the following matters:
`
`Nuance Communications, Inc. v. Vlingo Corp, United States District Court, D.
`
`Mass., 09-11414-RWZ, and Ultratec, Inc., et al. v. Sorenson Comm., Inc., et al.,
`
`W.D. Wisc., 3:14-cv-00066-JDP.
`
`C. Qualifications and Professional Experience
`I am currently Chief Executive Officer (CEO) of Big Tech Strategy.
`4.
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`
`
`1
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`5.
`
`I received a Bachelor of Science degree in Physics in 1985, a Master
`
`of Science degree in Computer Science in 1992, and a Doctor of Philosophy
`
`degree in Computer Science in 1997, all from Carnegie Mellon University. My
`
`Ph.D. thesis was entitled “Error-Responsive Feedback Mechanisms for Speech
`
`Recognizers.”
`
`6.
`
`From 1993 to 1997, I worked as the President of Human Language
`
`Systems, LLC in Pittsburgh, PA. Human Language Systems provided consulting
`
`services in speech and natural language processing technology. At Human
`
`Language Systems, I was responsible for providing strategic consulting, project
`
`management, and implementation services for speech recognition, natural language
`
`understanding, and spoken language systems to a number of private corporations
`
`and public institutions.
`
`7.
`
`In 1998, I worked as a Researcher for LIMSI/CNRS, Université Paris
`
`XI, a French National Research Laboratory in Orsay, France. There, I performed
`
`research in spoken language understanding systems in French and English.
`
`8.
`
`From 1999 to 2001, I worked as the Director of Operations, EMEA
`
`for SpeechWorks International, which provided spoken and natural language
`
`interactive systems for call center and telecommunications automation. I founded
`
`the European division of SpeechWorks International, eventually growing the
`
`2
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`operation to a staff of 30 and annual sales of $5 million. During my time in this
`
`position, I led the professional services and technical sales teams and was
`
`responsible for modifying SpeechWorks’ products to fit the European market,
`
`which included developing localized speech recognition products for French, UK
`
`English, and German languages, developing European-specific user interface
`
`development and testing methods, and integrating speech recognition software into
`
`call centers in France, the UK, and Germany.
`
`9.
`
`In 2002, I worked as the Vice President of Product Management and
`
`Partnerships at Rhetorical Systems, Ltd., in Edinburgh, Scotland. Rhetorical
`
`Systems, Ltd. provided text-to-speech software and professional services. There, I
`
`built professional services and sales engineering teams for call center and
`
`telecommunications markets.
`
`10.
`
`In 2002, I founded NeoSpeech, Inc., which specialized in speech
`
`technology and applications software, and served in the role of founding CEO until
`
`2004, the year the application that became the ’124 Patent was filed. At
`
`NeoSpeech, I managed the development and localization of text-to-speech
`
`software products for the U.S. market.
`
`11. Between 2005 and 2010, I was employed by Accenture in various
`
`roles, including managing the launch of the Accenture Technology Lab in India,
`
`3
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`which was the group responsible for developing IT vision, strategy, and innovation
`
`for the Asian and Middle Eastern markets. In this role, I oversaw the construction
`
`of Accenture’s laboratory space in Bangalore, which was eventually utilized to
`
`develop innovations in massive enterprise software and database systems, systems
`
`integration, software engineering and testing, large scale database and application
`
`management, and mapping and management of enterprise software architectures
`
`and communications pathways. After completion of a three-year assignment in
`
`India, I moved to California with Accenture in order to co-found the then-new joint
`
`venture between Accenture and Cisco, The Accenture Cisco Business Group
`
`(ACBG). I led the Accenture-side team in creating and launching a shared and
`
`mutually operated business with Cisco in the virtualized/distributed data center
`
`space.
`
`12. Since 2010, I have been CEO of Big Tech Strategy, which specializes
`
`in software design and technology strategy consulting. My responsibilities include
`
`developing and implementing go-to-market strategies for early stage clients
`
`developing software products in various technology spaces including speech and
`
`natural language processing, data center management and cloud computing,
`
`enterprise software, “big data” analytics, network security, and architecture
`
`engineering and construction. Big Tech Strategy provides consulting services to
`
`4
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`inventors of software and software controlled systems in both large companies and
`
`startups. I specialize in working with inventors to design and deploy new and
`
`innovative products in a manner that assures market adoption and eventual
`
`profitability. Over the past few years, I have worked closely with several
`
`companies focused on natural language processing and speech processing as
`
`applied to user interfaces deployed on mobile communications devices, and which
`
`are implemented on supporting distributed systems.
`
`13. My curriculum vitae, which is attached as Appendix A, further
`
`provides a more detailed summary of my background and experience, and
`
`additionally includes a list of my twenty-five (25) academic publications in the
`
`field of speech and natural language processing.
`
`14. By virtue of the above experience, I have gained a detailed
`
`understanding of the technology that is at issue in this proceeding. I believe I am
`
`qualified to provide opinions about how one of ordinary skill in the art would have
`
`interpreted and understood the ’124 Patent and the art relied upon by the Petitioner
`
`at the time of the invention of the ’124 Patent, as discussed below.
`
`D.
`15.
`
`Summary of My Study
`I am aware that the Petition for Inter Partes Review (Paper 2,
`
`hereafter “Petition”) filed in the above-identified proceeding asserts two grounds
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`of invalidity of claims of the ’124 Patent (Ex. 1001). I understand that the first
`
`ground of invalidity (“Ground 1”) is based on the combination of U.S. Patent No.
`
`7,003,463 (“Maes”) (Ex. 1005) and U.S. Patent Pub. No. 2003/0046061
`
`(“Preston”) (Ex. 1006). I understand that the second ground of invalidity
`
`(“Ground 2”) is based on the combination of U.S. Patent No. 7,027,975
`
`(“Pazandak”) (Ex. 1007), U.S. Patent Pub. No. 2002/0072918 (“White”) (Ex.
`
`1008), and U.S. Patent No. 7,085,708 (“Manson”) (Ex. 1009).
`
`16.
`
`I have reviewed the ’124 Patent, the Petition, the Declaration of Dr.
`
`Jason Flinn, Ph.D. (“the Flinn Report”) (Ex. 1002), the references relied upon for
`
`Ground 1 and Ground 2, as well as each reference cited by the Petition and/or the
`
`Flinn Report.
`
`17. My opinions are set forth below, and are based on my years of
`
`education, research, and experience, as well as my investigation and study of the
`
`materials identified above. I make these statements based upon facts and matters
`
`within my own knowledge or on information provided to me by others. All such
`
`facts and matters are true to the best of my knowledge and belief.
`
`II. RELEVANT LEGAL STANDARDS
`
`18. My understanding of the relevant legal standards is based on
`
`information provided to me by Patent Owner’s counsel.
`
`6
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`A. Claim Construction
`I understand that in an inter partes review proceeding, the claims of a
`19.
`
`non-expired patent are construed from the perspective of one of ordinary skill in
`
`the art at the time of the claimed invention and are given their broadest reasonable
`
`construction consistent with the specification.
`
`B. Obviousness
`It is my understanding that an invention is unpatentable if the
`20.
`
`differences between the invention and the prior art are such that the subject matter
`
`of the invention as a whole would have been obvious at the time the invention was
`
`made to a person having ordinary skill in the art. I further understand that
`
`obviousness is determined by evaluating: (1) the scope and content of the prior art,
`
`(2) the differences between the prior art and the claim, (3) the level of ordinary
`
`skill in the art, and (4) secondary considerations of nonobviousness. To establish
`
`obviousness based on a combination of prior art references, it is my understanding
`
`that a petitioner must identify a specific combination that teaches all limitations
`
`and establish that a person of ordinary skill in the art at the time of the claimed
`
`invention would have found it obvious to make that combination.
`
`21. To guard against hindsight and an unwarranted finding of
`
`obviousness, I understand that an important component of any obviousness inquiry
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`is whether the petitioner has identified any teaching, suggestion, or motivation that
`
`would have prompted a person of ordinary skill in the art to make the claimed
`
`combination and have a reasonable expectation of success in doing so. I
`
`understand that this test should not be rigidly applied, but can be an important tool
`
`to avoid the use of hindsight in the determination of obviousness.
`
`22.
`
`I further understand that the teaching, suggestion, or motivation may
`
`be found explicitly or implicitly: (1) in the prior art; (2) in the knowledge of those
`
`of ordinary skill in the art that certain references, or disclosures in those references,
`
`are of special interest or importance in the field; or (3) from the nature of the
`
`problem to be solved. Additionally, I understand that the legal determination of
`
`the motivation to combine references allows recourse to logic, judgment, and
`
`common sense. In order to resist the temptation to read into prior art the teachings
`
`of the invention in issue, however, it should be apparent that “common sense”
`
`should not be conflated with what appears obvious in hindsight.
`
`23.
`
`I understand that it is improper to combine references where the
`
`references teach away from their combination. I understand that a reference may
`
`be said to teach away when a person of ordinary skill in the relevant art, upon
`
`reading the reference, would be discouraged from following the path set out in the
`
`reference, or would be led in a direction divergent from the path that was taken by
`
`8
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`the applicant. I further understand that if the teachings of a prior art reference
`
`would lead a person of ordinary skill in the art to make a modification that would
`
`render another prior art device inoperable, then such a modification would
`
`generally not be obvious. I also understand that if a proposed modification would
`
`render the prior art invention being modified unsatisfactory for its intended
`
`purpose, then there would have been no suggestion or motivation to make the
`
`proposed modification.
`
`III. ONE OF ORDINARY SKILL IN THE ART
`
`24.
`
`I understand that Petitioner and the Flinn Report have alleged that a
`
`person of ordinary skill in the art in the field of the invention claimed in the ’124
`
`Patent would have had “a Bachelor’s degree or equivalent in computer science,
`
`electrical engineering, or a similar related field, as well as 1-2 years of experience
`
`working with natural language programming.” (Petition at 4; Ex. 1002 at ¶ 14).
`
`25.
`
`I believe I am qualified based on my education and experience,
`
`discussed above, to render opinions from the perspective of a person of ordinary
`
`skill in the art according to Petitioner’s proposed definition, and for the purposes of
`
`my opinions herein, I have used this definition. In particular, I have read the ’124
`
`Patent, Maes, Preston, Pazandak, White, and Manson, and have considered their
`
`disclosures from the perspective of such a person of ordinary skill at the time of the
`
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`invention of the ’124 Patent. Unless otherwise stated, my statements made herein
`
`refer to the knowledge of one of ordinary skill in the field of the invention claimed
`
`in the ’124 Patent.
`
`IV. OVERVIEW OF THE ’124 PATENT
`
`26. The ’124 Patent, entitled “Natural Language for Programming a
`
`Specialized Computing System,” is directed to a method and corresponding system
`
`for “programming a mobile communication device based on a high-level code
`
`comprising operative language [].” (Ex. 1001, Title, Abstract). The ’124 Patent
`
`describes a way for a user to control and/or program a mobile communication
`
`device (such as a cell phone) by providing high level inputs in a natural human
`
`language. (Id. at Abstract, 1:55-58).
`
`27. The ’124 Patent describes that the natural language input is processed
`
`and automatically converted into low level executable code that runs on the mobile
`
`communication device. (Id. at Abstract, 2:1-13, 5:5-10, FIG. 2). The approach
`
`described in the ’124 Patent eliminates the need for the user to interact at a low
`
`level with menu items available down at the operating system level of the mobile
`
`communication device. (See id. at 8:59-67, 9:47-10:4). This makes it possible for
`
`users to control or program the device using high level and natural human
`
`language, as opposed to low level technical controls or code.
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`28. As described in the ’124 Patent, a user provides “[h]igh-level code
`
`150 [which] may comprise one or more sentences, wherein each sentence
`
`comprises at least one operative language (i.e. keyword) defining an instruction for
`
`a function or an operation to be performed. In one embodiment, the sentences also
`
`comprise keywords defining conditions or relationships based on which an
`
`operation is performed.” (Id. at 4:17-23). The system and method described in the
`
`’124 Patent allows a user to provide high level inputs in a natural human language
`
`without making any limiting assumptions about the content of the high-level code.
`
`The approach described in the ’124 Patent supports an unlimited range of natural
`
`language inputs from a user.
`
`29. To process the possible range of natural language inputs from a user,
`
`the ’124 Patent relies, in part, upon the automated determination of both the level
`
`of complexity and the implementation of the high level input as it arrives, and then
`
`also upon designating which application software will be used to process the input.
`
`(Id. at 4:58-5:4, 9:14-17, 10:18-21). Given the wide range of words and intentions
`
`that might be present in the user’s high level inputs, the processing required to
`
`respond appropriately might be determined to take place in a specific fashion
`
`available in a specific place in the network. The ’124 Patent explicitly relies upon
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`looking at the high-level code itself for its complexity and implementation in order
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`to proceed in the best manner to complete its processing. (Id.)
`
`30. Additionally, to process the high-level code, the ’124 Patent relies on
`
`a specific parsing technique commonly referred to as “keyword spotting” or
`
`“keyword searching,” which scans through the input looking for particular
`
`keywords. (Id. at Abstract, 2:1-9, 5:31-61, 9:1-9, 10:5-13). The ’124 Patent
`
`discloses the use of keyword spotting on the input high-level code, looking for
`
`keywords indicative of “operative language” in the input that corresponds to
`
`operations of the mobile communication device and keywords indicative of
`
`“relationships and conditions corresponding to the operative language.” (Id.)
`
`31. The ’124 Patent describes that the high-level code that is input by the
`
`user is processed to produce executable code. (Id. at Abstract, 2:8-9, FIG. 2). Not
`
`all of the computation for the processing of the high-level code is required to
`
`happen on the mobile communication device. The ’124 Patent describes in detail a
`
`system and method which, depending on the complexity and implementation of the
`
`input high-level code, processes the input high-level code on a mobile
`
`communication device, a server attached to the mobile communication device via a
`
`network, or a combination of both. (See id. at 1:55-2:55, 4:49-5:4, FIGS. 1-2).
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`V. OPINION ON CLAIM CONSTRUCTION
`
`32.
`
`I understand that claim construction is the common terminology used
`
`to describe the interpretation of claim terms. It is also my understanding that in
`
`this inter partes review proceeding, the claim terms are to be given their broadest
`
`reasonable interpretation consistent with the specification and file history of the
`
`’124 Patent, as understood by one of ordinary skill in the art.
`
`33.
`
`It is my understanding that Petitioner has proposed a construction for
`
`the term “operative language” as meaning “language associated with one or more
`
`operations to be performed.” (Petition at 7). I have been instructed to adopt, and
`
`have adopted, Petitioner’s construction for the purposes of my opinions.
`
`34.
`
`It is also my understanding that Petitioner has alleged that certain
`
`terms should be interpreted as means-plus-function claim terms and has proposed
`
`corresponding structures for each term. (Petition at 8-13).
`
`35.
`
`I understand that Petitioner proposes the term “means for receiving a
`
`high-level code comprising one or more keywords,” as recited in claim 6, includes
`
`“a user interface, including a keypad, pointing device, touchscreen, keyboard,
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`microphone, or equivalents thereof.” (Petition at 9). I have been instructed to
`
`adopt, and have adopted Petitioner’s proposal for the purposes of my opinions.
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`36. Further, I understand that Petitioner proposes that the following claim
`
`terms, recited in claim 6, include “software running on a processor configured to
`
`perform the identified functions or equivalents thereof”: “means for parsing the
`
`high-level code for the keywords to recognize the operative language associated
`
`with controlling one or more operations of the mobile communication device”;
`
`“means for determining at least one operation associated with the operative
`
`language”; “means for determining whether high-level code comprises keywords
`
`defining one or more relationships and conditions corresponding to the operative
`
`language”; “means for producing an executable code”; “means for determining
`
`level of complexity and implementation of the high-level code”; and “means for
`
`designating an application software to process the high-level code.” I have been
`
`instructed to adopt, and have adopted, Petitioner’s proposals for the purposes of
`
`my opinions.
`
`VI. GROUNDS BASED ON MAES AND PRESTON
`
`37.
`
`It is my understanding that the Petitioner has alleged that the
`
`combination of Maes and Preston renders claims 1-10 of the ’124 Patent
`
`unpatentable. (Petition at 2). Having reviewed, among other things, Maes,
`
`Preston, the Petition, and Petitioner’s support for its allegations, it is my opinion
`
`that the combination of Maes and Preston as presented by the Petitioner does not
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`render obvious claims 1-10 of the ’124 Patent. Particularly, the combination of
`
`Maes and Preston does not disclose or suggest every element of independent
`
`claims 1 and 6 as alleged in the Petition.
`
`A.
`
`Summary of the Asserted References
`1. Maes
`38. Maes is entitled “System and Method for Providing Network
`
`Coordinated Conversational Services.” Maes describes a “system and method for
`
`providing automatic and coordinated sharing of conversational resources, e.g.,
`
`functions and arguments, between network-connected servers and devices and their
`
`corresponding applications.” (Ex. 1005 at Abstract). Generally, Maes describes a
`
`computing system architecture (including both software and hardware) that
`
`automates control of load assignment and load distribution for computational tasks
`
`rendered in support of requests from third party applications to provide
`
`conversational services.
`
`39. The third party applications referred to in Maes as the source of
`
`requests for conversational services would have been understood to be software
`
`applications that allow a human to interact with an artificial system using his or her
`
`own natural language. Maes provides to these applications access conversational
`
`services that are, in general, complex, resource-intensive, and expensive to operate,
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`such as speech recognition, natural language understanding, text-to-speech
`
`generation, natural language generation, and speaker identification. (See, e.g., id.
`
`at 1:49-60, 4:24-29, 4:57-62, 8:13-16). Maes does not describe how these
`
`conversational services are designed and/or how each functions. Instead, Maes
`
`focuses on describing a system and method for sharing these services among
`
`networked devices.
`
`40.
`
`In its background, Maes explains that “with the emergence of
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`pervasive computing, it is expected that billions of low resource client devices
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`(e.g., PDAs, smartphones, etc.) will be networked together.” (Id. at 1:36-38).
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`Additionally, Maes expects that due to their limited resources, client devices may
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`not be able to perform complex conversational tasks. (Id. at 1:50-60). To solve
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`this problem, Maes expresses the need for “a system and method that allows a
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`network device with limited resources to perform complex specific conversational
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`tasks automatically using networked resources in a manner which is automatic and
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`transparent to a user.” (Id. at 2:27-31).
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`41. Maes describes how various conversational services (speech
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`recognition, natural language understanding, text-to-speech, etc.) offered by
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`networked devices can be catalogued and deployed in a distributed fashion, and
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`how automated location and execution of these services can be accomplished
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`whenever a request arrives for the specific use of one of the available services.
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`42. The invention described in Maes is therefore “directed to a system and
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`method for providing automatic and coordinated sharing of conversational
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`resources between network-connected servers and devices (and their corresponding
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`applications).” (Id. at 2:35-38). Maes describes a system in which networked
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`devices are made “conversationally aware” of each other by using conversational
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`network protocols to transmit messages, processed by dialog managers, to
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`automatically share conversational resources and functions among the networked
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`devices, and the method of operating such a system. (Id. at 2:35-48, 5:19-25).
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`Preston
`2.
`43. Preston is entitled “Apparatus for Automatically Generating Source
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`Code.” Preston describes, “[a] method of automatically generating software from
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`one or more predefined functions in accordance with an input statement entered in
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`natural language.” (Ex. 1006 at Abstract). The invention in Preston “relates to
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`apparatus for automatically generating source code, and is particularly, but not
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`exclusively, suitable for generating source code for communication services.” (Id.
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`at [0001]).
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`44. Generally, Preston is about replacing human computer programmers
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`where possible – in cases where the programmer would have been working on
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`simpler or well understood programming tasks. Preston additionally identifies that
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`there are “many situations where it is desirable for a non-programmer to be able to
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`program a system so that it can subsequently act on his or her behalf without
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`further interaction.” (Id. at [0007]). Preston explains that a non-programmer
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`should therefore be able to program a system without the need to learn a particular
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`programming language. (Id. at [0008]).
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`45. Preston therefore describes a method to allow a non-programmer user
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`to input a natural language instruction and have it be analyzed and used to put
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`together source code customized for carrying out the user’s wishes. (Id. at [0049]).
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`As described by Preston, a user inputting a natural language instruction to create
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`source code is only allowed to draw upon a fixed, limited library of pre-defined
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`and pre-existing functions. But, if the user is willing to choose from the limited
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`options made available, then Preston describes a way to take in natural language as
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`input and produce source code as output.
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`46.
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`In Preston, certain natural language descriptions are associated with
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`pre-defined functions and their relationships are stored in data storage. (Id. at
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`[0057]). A user inputs natural language and the method determines whether the
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`input natural language is associated with any pre-defined functions in the data
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`storage. (Id. at [0061]). If the user’s input is associated with a function contained
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`in the data storage, a code generator generates source code corresponding to the
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`pre-defined function. (Id.)
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`B.
`
`Petitioner’s Proposed Combination of Maes and Preston Does Not
`Render Obvious Claims 1 and 6
`1. Maes and Preston do not disclose or suggest “parsing the
`high-level code for the keywords” as alleged by Petitioner
`
`47.
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`I understand that in support of Petitioner’s allegation that the
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`combination of Maes and Preston renders obvious claims 1 and 6, Petitioner has
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`exclusively relied on Maes for its purported teaching of:
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`[means for] parsing the high-level code for the keywords to recognize
`the operative language associated with controlling one or more
`operations of the mobile communication device.
`
`In my opinion, the combination of Maes and Preston presented by the Petitioner
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`cannot render obvious claims 1 and 6, at least because Maes does not disclose or
`
`suggest “parsing the high-level code for the keywords” as alleged in the Petition.
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`48. A person of ordinary skill in the art would understand that the step of
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`“parsing the high-level code for the keywords” as recited in claims 1 and 6 refers
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`to a particular parsing technique that requires parsing an input (i.e., high-level
`
`code) to identify keywords. This parsing technique is commonly referred to in the
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`art as “keyword spotting” or “keyword searching.” A person of ordinary skill in
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`the art would understand that when parsing for keywords, the parser does not
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`account for or rely upon items in the input (high-level code) that are not keywords,
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`but rather selectively and individually identifies particular items in the input
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`sequence (i.e., the keywords).
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`49. A person of ordinary