Used in Lieu of PTO/SB/08NB
`(Based on PTO 10-07 version)
`
`Substitute for form 1449/PTO
`
`INFORMATION DISCLOSURE
`STATEMENT BY APPLICANT
`
`(Use as many sheets as necessary)
`
`Sheet I
`
`1
`
`I of I
`
`1
`
`Application Number
`
`FIiing Date
`
`Complete if Known
`Not yet assigned
`Concurrently Herewith
`Guy Larri
`Not yet assigned
`Not yet assigned
`Attorney Docket Number M0025.0369-C
`
`First Named Inventor
`
`Art Unit
`
`Examiner Name
`
`Examiner
`Initials*
`
`Document Number
`Cite
`No.1 Number-Kind Code2
`
`( if known)
`
`Publication Date
`MM-YYYY
`
`Name of Patentee or
`Applicant of Cited Document
`
`Pages, Columns, Lines, Where
`Relevant Passages or Relevant
`Figures Appear
`
`U.S. PATENT DOCUMENTS
`
`A1
`A1
`
`5,881,312
`7,328,153
`2004/0111264
`2003/0061046
`6.374.220
`9,076,441
`8,352,262
`7,979,277
`8,036,890
`8,612,227
`
`03-1999
`02-2008
`06-2004
`03-2003
`04-2002
`07-2015
`01-2013
`07-2011
`10-2011
`12-2013
`
`Dulono
`Wells et al.
`Wang et al.
`Zhao et al.
`Kao
`Larri et al.
`Larri et al.
`Larri et al.
`Catchpole
`Kato
`
`FOREIGN PATENT DOCUMENTS
`Publication
`ForeiQn Patent Document
`Examiner Cite
`Date
`No.1 Country Code'-Number'-Kind Code' /if known) MM-YYYY
`Initials*
`
`Name of Patentee or
`Applicant of Cited Document
`
`GB2391679A
`
`EP 1 178 466 A2
`
`WO 01/75862 A2
`WO 01/48737 A2
`
`GB 2 333 172 A
`WO 03/067572
`A2
`
`02-2004
`
`02-2002
`
`10-2001
`07-2001
`07-1999
`
`08-2003
`
`Pages, Columns, Lines,
`
`Where Relevant Passages r
`
`Or Relevant Figures Appear
`
`II
`
`~
`
`*EXAMINER: Initial if reference considered, whether or not citation is in confonmance with MPEP 609. Draw line through citation if not in confonmance and not
`considered. Include copy of this form with next communication to applicant. 1 Applicant's unique citation designation number (optional). 'See Kinds Codes of
`USPTO Patent Documents at www.uspto.gov or MPEP 901.04. 3 Enter Office that issued the document, by the two-letter code (WIPO Standard ST.3). 4 For
`Japanese patent documents, the indication of the year of the reign of the Emperor must precede the serial number of the patent document. 5 Kind of document
`by the appropriate symbols as indicated on the document under WIPO Standard ST.16 if possible. 6 Applicant is to place a check mark here if English language
`Translation is attached.
`
`Examiner
`Initials
`
`Cite
`No. 1
`
`NON PATENT LITERATURE DOCUMENTS
`Include name of the author (in CAPITAL LETTERS), title of the article (when appropriate), title of the item (book,
`magazine, journal, serial, symposium, catalog, etc.), date, page(s), volume-issue number(s), publisher, city
`and/or country where published.
`IEEE Transactions
`Language Recognition
`on DSP Array Processor"
`Glinski et al., "Spoken
`Systems, Vol. 5, No. 7, PP. 697-703,
`July 1, 1994.
`Parallel and Distributed
`S. Chatterjee
`et al., "Connected
`Speech Recognition
`on a Multiple Processor
`ICASSP
`89, pp, 774-777, Mav 23, 1989.
`
`Pipeline."
`
`on
`
`T2
`
`*EXAMINER: Initial if reference considered, whether or not citation is in confonmance with MPEP 609. Draw line through citation if not in confonmance and not
`considered. Include copy of this fonm with next communication to applicant.
`
`'Applicant's unique citation designation number {optional). 'Applicant is to place a check mark here if English language Translation is attached.
`
`I Examiner I
`
`Signature
`
`'Date
`Considered
`
`DSMDB-3348573 vi
`
`IPR2023-00035
`Apple EX1002 Page 1
`
`

`

`Electronic Patent Application Fee Transmittal
`
`Application Number:
`
`Filing Date:
`
`Title of Invention:
`
`A SPEECH RECOGNITION CIRCUIT AND METHOD
`
`First Named Inventor/Applicant Name:
`
`Guy Larri
`
`Filer:
`
`Stephen A. Soffen/Madeline Baker
`
`Attorney Docket Number:
`
`M0025.0369-c
`
`Filed as Small Entity
`
`Filing Fees for Utility under 35 USC 111 (a)
`
`Description
`
`Fee Code
`
`Quantity
`
`Amount
`
`Sub-Total in
`USO($)
`
`Basic Filing:
`
`Utility filing Fee (Electronic filing)
`
`Utility Search Fee
`
`Utility Examination Fee
`
`4011
`
`2111
`
`2311
`
`1
`
`1
`
`1
`
`70
`
`300
`
`360
`
`70
`
`300
`
`360
`
`Pages:
`
`Claims:
`
`Miscellaneous-Filing:
`
`Petition:
`
`Patent-Appeals-and-Interference:
`
`IPR2023-00035
`Apple EX1002 Page 2
`
`

`

`Description
`
`Fee Code
`
`Quantity
`
`Amount
`
`Sub-Total
`USO($)
`
`in
`
`Post-Allowance-and-Post-Issuance:
`
`Extension-of-Time:
`
`Miscellaneous:
`
`Total in USD ($)
`
`730
`
`IPR2023-00035
`Apple EX1002 Page 3
`
`

`

`Electronic Acknowledgement Receipt
`
`EFSID:
`
`Application Number:
`
`22793233
`
`14788164
`
`International Application Number:
`
`Confirmation Number:
`
`1250
`
`Title of Invention:
`
`A SPEECH RECOGNITION CIRCUIT AND METHOD
`
`First Named Inventor/Applicant Name:
`
`Guy Larri
`
`Customer Number:
`
`24998
`
`Filer:
`
`Stephen A. Soffen/Madeline Baker
`
`Filer Authorized By:
`
`Stephen A. Soffen
`
`Attorney Docket Number:
`
`M0025.0369-c
`
`Receipt Date:
`
`30-JUN-2015
`
`Filing Date:
`
`Time Stamp:
`
`17:57:34
`
`Application Type:
`
`Utility under 35 USC 111 (a)
`
`Payment information:
`
`Submitted with Payment
`
`Payment Type
`
`Payment was successfully received in RAM
`
`RAM confirmation Number
`
`Deposit Account
`
`Authorized User
`
`yes
`
`Credit Card
`
`$730
`
`6125
`
`The Director of the USPTO is hereby authorized
`
`to charge indicated
`
`fees and credit any overpayment as follows:
`
`IPR2023-00035
`Apple EX1002 Page 4
`
`

`

`File Listing:
`
`Document
`Number
`
`1
`
`Document Description
`
`File Name
`
`File Size(Bytes)/
`Message Digest
`
`Multi
`Part /.zip
`
`Pages
`(if appl.)
`
`M0369c.pdf
`
`yes
`
`107
`
`4739441
`
`fS ab44625 7 e08ebfb8722eb57 d b09d 1 d 89~
`e732f
`
`Multipart Description/PDF files in .zip description
`
`Document Description
`
`Start
`
`End
`
`Transmittal of New Application
`
`Application Data Sheet
`
`Appendix to the Specification
`
`Claims
`
`Abstract
`
`Drawings-only black and white line drawings
`
`Oath or Declaration filed
`
`Power of Attorney
`
`Transmittal Letter
`
`Information Disclosure Statement (IDS) Form (SB0S)
`
`1
`
`6
`
`70
`
`71
`
`72
`
`99
`
`103
`
`104
`
`106
`
`107
`
`1
`
`2
`
`7
`
`71
`
`72
`
`73
`
`100
`
`104
`
`105
`
`107
`
`35187
`
`Warnings:
`
`Information:
`
`2
`
`Fee Worksheet (SB06)
`
`fee-info.pdf
`
`no
`
`2
`
`172c6a028f9412e4020ed957ba8bb8ca324
`bbbb4
`
`Warnings:
`
`Information:
`
`Total Files Size (in bytes)
`
`4774628
`
`IPR2023-00035
`Apple EX1002 Page 5
`
`

`

`This Acknowledgement Receipt evidences receipt on the noted date by the USPTO of the indicated documents,
`characterized by the applicant, and including page counts, where applicable. It serves as evidence of receipt similar to a
`Post Card, as described
`in MPEP 503.
`
`New Applications Under 35 U.S.C. 111
`for a filing date (see 37 CFR
`includes the necessary components
`If a new application
`is being filed and the application
`1.53(b)-(d) and MPEP 506), a Filing Receipt (37 CFR 1.54) will be issued in due course and the date shown on this
`Acknowledgement Receipt will establish the filing date of the application.
`
`National Stage of an International Application under 35 U.S.C. 371
`is compliant with the conditions of 35
`If a timely submission
`to enter the national stage of an international application
`U.S.C. 371 and other applicable requirements a Form PCT/DO/EO/903 indicating acceptance of the application as a
`national stage submission under 35 U.S.C. 371 will be issued in addition to the Filing Receipt, in due course.
`
`New International Application Filed with the USPTO as a Receiving Office
`for
`includes the necessary components
`If a new international application
`is being filed and the international application
`an international
`filing date (see PCT Article 11 and MPEP 181 O), a Notification of the International Application Number
`and of the International Filing Date (Form PCT/RO/1 OS) will be issued in due course, subject to prescriptions concerning
`national security, and the date shown on this Acknowledgement Receipt will establish the international
`filing date of
`the application.
`
`IPR2023-00035
`Apple EX1002 Page 6
`
`

`

`POWER OF ATTORNEY TO PROSECUTE APPLICATIONS BEFORE THE USPTO
`As the Applicant and/or Assignee I hereby appoint:
`
`24998
`
`I
`GJ :;otmoaera associ,red w,lhthe Customec Numbec: I
`D Practitioner{s) named below {if more than ten patent practitioners are to be named, then a customer number must be used): I
`
`Name
`
`Registration
`Number
`
`Name
`
`Registration
`Number
`
`as attorney(s) or agent(s)"to represent the Applicant and/or Assignee before the United States Patent and
`Trademark Office (USPTO) in connection with any and all patent applications assigned to the Applicant and/or
`Assignee, under an obligation to be assigned to the Applicant and/or Assignee, or for which the Applicant and/or
`Assignee has a sufficient proprietary interest.
`
`Assignee and/or Applicant Name and Address,
`Zentian Limited
`Paddock Row
`Elsworth, Cambridge
`Cambridgeshire CB23 4JG
`United Kingdom
`
`The practitioners appointed in this form are authorized to act on behalf of the
`assignee and/or applicant to transact all business in the United States Patent
`and Trademark Office.
`
`SIGNATURE of Assignee and/or Applicant
`The individual whose signature and'title is supplied below is authorized to act on b~halfof the assig11ee and/or applicant
`
`Signature
`Name
`
`Title and Company
`
`l;'j(~
`
`li1 u
`S uy Lt\RR-1
`l) 1 r {.c.,\o<, Z.e.nt(o-.n L~fl'\·1-\-~
`
`Date 28 JvJ1
`Telephone 0TH 8 424-B~S 1~U\<.
`
`20\ Cr
`
`DSMDB-3259765 V1
`
`IPR2023-00035
`Apple EX1002 Page 7
`
`

`

`Docket No.: M0025.0369-C
`(PATENT)
`
`IN THE UNITED STATES PATENT AND TRADEMARK OFFICE
`
`In re Letters Patent of:
`Guy Larri et al.
`
`Confirmation No.: Not yet assigned
`
`Application No.: Not yet assigned
`
`Group Art Unit: Not yet assigned
`
`Issued: Concurrently Herewith
`
`Examiner: Not yet assigned
`
`For: A SPEECH RECOGNITION CIRCUIT AND
`METHOD
`
`INFORMATION DISCLOSURE STATEMENT {IDS)
`
`Commissioner for Patents
`P.O. Box 1450
`Alexandria, VA 22313-1450
`
`Dear Madam:
`
`Pursuant to 37 CFR 1.56, 1.97 and 1.98, the attention of the Patent and Trademark
`
`Office is hereby directed to the references listed on the attached PTO/SB/08. It is respectfully
`
`requested that the information be expressly considered during the prosecution of this application,
`
`and that the references be made of record therein and appear among the "References Cited" on any
`
`patent to issue therefrom.
`
`This Information Disclosure Statement accompanies the continuation patent application
`
`submitted herewith. Those documents cited in the attached form PTO/SB/08 that were previously
`
`cited by or submitted to the Office in prior application number 13/735,091, filed July 7, 2013 and/or
`
`the parent applications thereof, and relied upon in this application for an earlier filing date under 35
`
`U.S.C. 120, are not supplied.
`
`DSMDB-3348571 vi
`
`IPR2023-00035
`Apple EX1002 Page 8
`
`

`

`Application No.: Not yet assigned
`
`Docket No.: M0025.0369-C
`
`In accordance with 37 CFR l.98(a)(2)(ii), Applicant has not submitted copies of U.S.
`
`patents and U.S. patent applications.
`
`In accordance with 37 CFR l .97(g), the filing of this Information Disclosure Statement
`
`shall not be construed to mean that a search has been made or that no other material information as
`
`defined in 37 CFR l.56(b) exists. In accordance with 37 CFR l.97(h), the filing of this Information
`
`Disclosure Statement shall not be construed to be an admission that any patent, publication or other
`
`information referred to therein is "prior art" for this invention unless specifically designated as such.
`
`It is submitted that the Information Disclosure Statement is in compliance with 3 7 CFR
`
`1.98 and the Examiner is respectfully requested to consider the listed references.
`
`Dated: June 30, 2015
`
`By=----=-----'-"---ll--1"-=::__
`Stephen A. Soffen
`Registration No.: 31,063
`DICKSTEIN SHAPIRO LLP
`1825 Eye Street, NW
`Washington, DC 20006-5403
`(202) 420-2200
`Attorney for Applicant
`
`2
`
`DSMDB-3348571 vi
`
`IPR2023-00035
`Apple EX1002 Page 9
`
`

`

`PTO/AIA/15 (07-12)
`Approved for use through 01/31/2014. 0MB 0651-0032
`U.S. Patent and Trademark Office. U.S. DEPARTMENT OF COMMERCE
`Under the Paperwork Reduction Act of 1995 no persons are required to respond to a collection of information unless it displays a valid 0MB control number
`I M0025.0369-C
`UTILITY
`I Guy Larri
`PATENT APPLICATION
`TRANSMITTAL
`
`Attorney
`
`Docket No.
`
`First
`
`Inventor
`
`Title
`
`A SPEECH RECOGNITION CIRCUIT AND METHOD
`
`(ONLY FOR NEW NONPROVISIONAL APPLICATIONS UNDER
`37 CFR 1.53(8))
`
`Express Mail Label No.
`
`I
`
`APPLICATION ELEMENTS
`See MPEP chapter 600 concerning utility patent application contents.
`
`Commissioner
`ADDRESS TO: P.O. Box 1450
`Alexandria, VA 22313-1450
`
`for Patents
`
`1. □ Fee Transmittal Form.
`(PTO/SB/17 or equivalent)
`2. 0 Applicant claims small entity status.
`3. 5J Specification.
`[Total Pages 66
`Both the claims and abstract must start on a new page
`4. 0 Drawing(s). (35 U.S.C. 113)
`(For information on the prefe/Ted arrangement. see MPEP § 608.01/a))
`27
`l
`---
`4
`5. Inventor's Oath or Declaration.
`l
`[Total Sheets
`(including substitute statements under 37 CFR 1.64 and assignments serving as an
`oath or declaration under 37 CFR 1.63/e))
`
`See 37 CFR 1.27.
`
`l
`
`[Total Sheets
`
`a. 0 Newly executed (original or copy)
`6. 0 Application Data Sheet. ·see Note below.
`
`b. DA
`
`copy from a prior application (37 CFR 1.63(d))
`
`See 37 CFR 1.76 (PTO/AIN14 or equivalent)
`7. □ CD-ROM or CD-R.
`In duplicate, large table or Computer Program /Appendix)
`D Landscape Table on CD
`
`8. Nucleotide and/or Amino Acid Sequence Submission.
`(if applicable, items a. - c. are required)
`
`b.
`
`Specification Sequence Listing on:
`
`a. D Computer Readable Form (CRF)
`i. D CD-ROM or CD-R (2 copies); or
`ii. D Paper
`c. D Statements verifying identity of above copies
`
`*Note:
`
`ACCOMPANYING APPLICATION PARTS
`
`9. D Assignment Papers. (cover sheet & document(s))
`
`Name of Assignee
`
`I
`I
`10. D 37 CFR 3.73(c) Statement. 0 Power of Attorney.
`11. D English Translation Document. /if applicable)
`12 0 Information Disclosure Statement.
`
`•
`
`(PTO/SB/08 or PT0-1449)
`
`(when there is an assignee)
`
`D Copies of citations attached
`
`13. D Preliminary Amendment.
`14. D Return Receipt Postcard.
`15_ D Certified Copy of Priority Document(s.)
`16. D Nonpublication Request.
`
`(MPEP § 503) (Should be specifically itemized)
`
`(if foreign priority is claimed)
`
`Under 35 U.S.C.122 (b)(2)(B)(i). Applicant must attach form PTO/SB/35 or
`equivalent.
`
`17. Oother:
`
`I
`
`I
`(1) Benefit claims under 37 CFR 1. 78 and foreign priority claims under 1.55 must be included in an Application Data Sheet (ADS).
`(2) For applications filed under 35 U.S.C. 111, the application must contain an ADS specifying the applicant if the applicant is an
`assignee, person to whom the inventor is under an obligation to assign, or person who otherwise shows sufficient proprietary
`interest in the matter. See 37 CFR 1.46(b).
`
`0 The address associated with Customer Number: I
`
`19. CORRESPONDENCE
`24998
`
`ADDRESS
`
`I OR D Correspondence address below
`
`Name
`
`Stephen A. Soffen
`DICKSTEIN SHAPIRO LLP
`
`Address 1825 Eye Street, NW
`
`City
`
`Country
`
`Signature
`
`Name
`/Print/Tvoe)
`
`l
`
`I State /
`Washington
`DC
`I Telephone I (202) 420-2200 I Email
`us
`Al:t9.Av<-'n.J~~)
`Stephen A. Soffen
`
`I
`Registration No. I
`
`/Attornev/Aaent\
`
`/ Zip Code/
`
`20006-5403
`
`I
`
`Date
`
`June 30, 2015
`31,063
`
`DSMDB-3348578 vl
`
`IPR2023-00035
`Apple EX1002 Page 10
`
`

`

`Application Data Sheet
`
`Inventor Information
`
`Inventor Number::
`
`Given Name::
`
`Family Name::
`
`1
`
`Guy
`
`Larri
`
`City of Residence::
`
`Cambridge
`
`Country of Residence::
`
`United Kingdom
`
`Street of mailing address::
`
`1 Cutter Ferry Lane
`
`City of mailing address::
`
`Cambridge
`
`Country of mailing address::
`
`United Kingdom
`
`Postal or Zip Code of mailing address:: CB4 1JR
`
`Inventor Number::
`
`Given Name::
`
`Family Name::
`
`City of Residence::
`
`2
`
`Mark
`
`Catchpole
`
`Prickwillow
`
`Country of Residence::
`
`United Kingdom
`
`Street of mailing address::
`
`Malahax, Ely Road
`
`City of mailing address::
`
`Prickwillow
`
`Country of mailing address::
`
`United Kingdom
`
`Postal or Zip Code of mailing address:: CB7 4UJ
`
`Page# 1
`
`New0 1/04/2013
`DSMDB-334858 I v I
`
`IPR2023-00035
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`
`

`

`Inventor Number::
`
`Given Name::
`
`Middle Name::
`
`Family Name::
`
`City of Residence::
`
`3
`
`Damian
`
`Kelly
`
`Harris-Dowsett
`
`Coventry
`
`Country of Residence::
`
`United Kingdom
`
`Street of mailing address::
`
`22 Hollis Road
`
`City of mailing address::
`
`Coventry
`
`Country of mailing address::
`
`United Kingdom
`
`Postal or Zip Code of mailing address::
`
`CV31AL
`
`Inventor Number::
`
`Given Name::
`
`Middle Name::
`
`Family Name::
`
`City of Residence::
`
`4
`
`Timothy
`
`Brian
`
`Reynolds
`
`Cambridge
`
`Country of Residence::
`
`United Kingdom
`
`Street of mailing address::
`
`City of mailing address::
`
`22 Camside
`
`Cambridge
`
`Country of mailing address::
`
`United Kingdom
`
`Postal or Zip Code of mailing address::
`
`CB4 1PQ
`
`DSMDB-3348581 vi
`
`Page# 2
`
`New0 1/04/2013
`
`IPR2023-00035
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`
`

`

`Correspondence Information
`
`Correspondence Customer Number::
`
`24998
`
`Application Information
`
`Application Type::
`
`Subject Matter::
`
`CD-ROM or CD-R?::
`
`Sequence submission?::
`
`Regular
`
`Utility
`
`None
`
`None
`
`Computer Readable Form (CRF)?::
`
`No
`
`Title::
`
`A SPEECH RECOGNITION CIRCUIT AND
`
`Attorney Docket Number::
`
`M0025.0369-C
`
`METHOD
`
`Request for Early Publication?::
`
`Request for Non-Publication?::
`
`Total Drawing Sheets::
`
`Small Entity?::
`
`Petition included?::
`
`Secrecy Order in Parent Appl.?::
`
`Authorization to Permit Access::
`
`No
`
`No
`
`27
`
`Yes
`
`No
`
`No
`
`No
`
`Representative Information
`
`Representative Customer Number::
`
`24998
`
`DSMDB-334858I vi
`
`Page# 3
`
`New0 1/04/2013
`
`IPR2023-00035
`Apple EX1002 Page 13
`
`

`

`Domestic Priority Information
`
`Application:: Continuity
`Type::
`
`Parent Application::
`
`Parent Filing
`Date::
`
`Status
`
`This
`Application
`
`13/735,091
`
`is a
`continuation of
`
`is a
`continuation of
`
`13/735,091
`
`01/07/2013
`
`Pat. 9,076,441
`
`13/162,128
`
`06/16/2011
`
`Pat. 8,352,262
`
`13/162, 128
`
`Is a divisional of 11/662,704
`
`03/14/2007
`
`Pat. 7.979,277
`
`PCT /GB2005/003554 09/14/2005
`
`11/662,704
`
`Is a national
`stage under 35
`USC 371 of
`
`Foreign Priority Information
`
`Country::
`
`Application number::
`
`Filing Date::
`
`Priority Claimed::
`
`United Kingdom
`
`0420464.0
`
`09/14/2004
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`Yes
`
`Applicant Information
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`Applicant Number::
`
`Applicant Type::
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`1
`
`Assignee
`
`Organization Name::
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`Zentian Limited
`
`Street of mailing address::
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`Paddock Row, Elsworth
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`City of mailing address::
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`Cambridge
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`Country of mailing address::
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`United Kingdom
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`Postal or Zip Code of mailing address:: CB23 4JG
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`Signature:
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`A signature of the applicant or representative is required in accordance with 37 CFR 1.33 and 10.18.
`Please see 37 CFR
`ture.
`Signature
`Name
`Print/T e
`
`June 30, 2015
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`31,063
`
`Stephen A. Soften
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`Date
`Registration No.
`Attorne / A ent
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`A SPEECH RECOGNITION CIRCUIT AND METHOD
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`This is a continuation of application Serial No. 13/735,091, filed January 7, 2013, now
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`Pat. 9,076,441, which is a continuation of application Serial No. 13/162, 128, filed June
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`16, 2011, now Pat. 8,352,262, which is a divisional of application Serial No.
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`11/662,704, filed March 14, 2007, now Pat. 7,979,277, which is a 371 of
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`PCT/GB2005/003554, filed September 14, 2005, which claims priority to UK
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`Application No. 0420464.0, filed September 14, 2004, the disclosures of- which are
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`hereby incorporated by reference in their entireties.
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`BACKGROUND OF THE INVENTION
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`1. Field of the Invention:
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`The present invention relates to speech recognition circuits and methods. These circuits
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`and methods have wide applicability, particularly for devices such as mobile electronic
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`devices.
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`2. Description of the Related Art:
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`There is growing consumer demand for embedded speech recognition in mobile
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`electronic devices, such as mobile phones, dictation machines, PDAs (personal digital
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`assistants), mobile games consoles, etc. For example, email and text message dictation,
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`note taking, form filling, and command and control applications are all potential
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`applications of embedded speech recognition.
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`However, when a medium to large vocabulary is required, effective speech recognition
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`for mobile electronic devices has many difficulties not associated with speech
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`recognition systems in hardware systems such as personal computers or workstations.
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`Firstly, the available power in mobile systems is often supplied by battery, and may be
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`severely limited. Secondly, mobile electronic devices are frequently designed to be as
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`small as practically possible. Thus, the memory and resources of such mobile embedded
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`systems tends to be very limited, due to power and space restrictions. The cost of
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`providing extra memory and resources in a mobile electronic device is typically much
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`higher than that for a less portable device without this space restriction. Thirdly, the
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`mobile hardware may be typically used in a noisier environment than that of a fixed
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`computer, e.g. on public transport, near a busy road, etc. Thus, a more complex speech
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`model and more intensive computation may be required to obtain adequate speech
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`recognition results.
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`These restrictions have made it difficult to implement effective speech recognition in
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`mobile devices, other than with very limited vocabularies.
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`Some prior art schemes have been proposed to increase the efficiency of speech
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`recognition systems, in an attempt to make them more suitable for use in mobile
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`technology.
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`In an article entitled "A low-power accelerator for the SPHINX 3 speech recognition
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`system", in University of Utah, International conference on Compilers, Architectures
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`and Synthesis for Embedded Systems, Nov 2003, Davis et al have proposed the idea of
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`using a special purpose co-processor for up-front calculation of the computationally
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`expensive Gaussian output probabilities of audio frames corresponding to particular
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`states in the acoustic model.
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`In an article entitled "Hardware Speech Recognition in Low Cost, Low Power Devices",
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`University of California, Berkeley, CS252 Class Project, Spring 2003, Sukun Kim et al
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`describe using special purpose processing elements for each of the nodes in the network
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`to be searched. This effectively implies having a single processing element for each
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`phone in the network. An alternative suggested by Sukun Kim et al is to provide a
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`processor for each state in the network.
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`In an article entitled "Dynamic Programming Search for Continuous Speech
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`Recognition" in IEEE Signal Processing Magazine, Sept 1999, Ney et al discuss
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`language model lookahead. Language model lookahead involves computation of a
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`language model factor for each node (i.e. phone) in the lexical tree. This technique is
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`also known as smearing. Each phone instance in the search network can be given a
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`language model factor when it is used in the lexical tree search. Ney et al show that for
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`an example bigram language model, the average number of states per 10 ms frame can
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`be reduced from around 168,000 states with no language model lookahead to around
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`8,000 states when language model lookahead is used. They also show that bigram
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`language model lookahead requires about a quarter of the states compared with uni gram
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`language model lookahead.
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`Although these prior art documents provide improvements to speech recognition in
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`embedded mobile technology, further improvement is still needed to provide a larger
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`vocabulary and better accuracy.
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`SUMMARY OF THE INVENTION
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`One aspect of the present invention provides a speech recognition circuit including a
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`circuit for providing state identifiers which identify states corresponding to nodes or
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`groups of adjacent nodes in a lexical tree, and for providing scores corresponding to
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`said state identifiers. The lexical tree includes a model of words. The speech recognition
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`circuit also has a memory structure for receiving and storing state identifiers identified
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`by a node identifier identifying nodes or groups of adjacent nodes, the memory structure
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`being adapted to allow lookup to identify particular state identifiers, reading of the
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`scores corresponding to the state identifiers, and writing back of the scores to the
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`memory structure after modification of the scores. An accumulator is provided for
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`receiving score updates corresponding to particular state identifiers from a score update
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`generating circuit which generates the score updates using audio input, for receiving
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`scores from the memory structure, and for modifying said scores by adding said score
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`updates to said scores. A selector circuit is used for selecting at least one node or group
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`of nodes of the lexical tree according to said scores.
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`One suitable type of hardware for the memory structure includes a content addressable
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`memory (CAM). A CAM is a memory unit which stores a series of data items using a
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`series of addresses. However, the memory is accessed by specifying a data item, such
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`that the CAM returns the corresponding address. This contrasts with a random access
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`memory (RAM) in which the memory is accessed by specifying an address, such that
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`the RAM returns the corresponding data item.
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`However, the memory structure is not limited to including a CAM. Other types of
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`hardware are also possible, to provide this functionality. For example, a single chip
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`which operates in the same way as a CAM and RAM may be used instead.
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`Embodiments of the present invention provide a solution to the problem of how to map
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`a lexical tree search to a CAM system architecture. The realisation by the present
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`inventors that certain speech recognition data structures can be mapped into the CAMs
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`allows a lexical tree search to be performed using a CAM system architecture.
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`Further embodiments of the invention include a counter for sequentially generating state
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`identifiers, and using said generated state identifiers to sequentially lookup said states in
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`the memory structure.
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`The node identifier may comprise a direct reference to the lexical tree. However, in
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`some embodiments, the node identifier for at least some of the states includes a pointer
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`to a node identifier for another state. For example, a state corresponding to the furthest
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`part of the search path in the lexical tree may be referenced by a node identifier which
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`directly links to a particular node or group of nodes in the lexical tree. In a lexical tree
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`comprising phones, using a state model of trip hones, the node identifier may indicate
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`the position of a triphone in the lexical tree.
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`However, in this example, for states occuring further back in the search path, instead of
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`supplying a node identifier linking directly to the lexical tree, instead a pointer to a node
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`identifier of another state may be supplied. E.g. a trip hone instance may have a pointer
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`to another triphone instance, which has a pointer to another triphone instance, which has
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`a pointer to a node or group of nodes in the lexical tree. Chains of reference may be set
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`up in this way, where only the last state in the chain has a direct pointer to the lexical
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`tree.
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`There may not be a one-to-one correspondence between the nodes of the lexical tree and
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`the node identifiers. This will occur for a branched lexical tree, where the nodes
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`represent monophones, but the acoustic model states represent triphones, i.e. groups of
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`three adjacent monophones. Then, paths of three monophones will have unique
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`identifiers to be stored in the memory structure, rather than single monophones having
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`unique identifiers.
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`Phone instance numbers may be generated, and used to uniquely label each phone
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`instance. They can be generated sequentially, using a counter. The phone instance
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`numbers may be used as pointers between phone instances to assist in node
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`identification. It is thus not essential to provide a direct node identifier for each phone
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`instance to directly indicate a location in the lexical tree. The dynamic network of phone
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`instances provided in the memory structure may thus include both direct and relative
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`references to the lexical tree.
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`The memory structure may be divided into one part which stores phone instance
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`identifiers and direct references to the lexical tree, and a second part which stores phone
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`instance identifiers and corresponding states. This can speed up the processing, by only
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`storing the phone instances which are furthest on in the lexical tree in the first part of
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`the memory structure.
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`The memory structure may also be divided into separately accessable units, to reduce
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`the amount to data in each unit, thereby decreasing the chance of finding the same two
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`states identifiers in different phone instances in any single memory unit, and increasing
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`the chance of some state identifiers being completely absent from any single memory
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`unit. This makes it easier to deal with the situation when the same two state identifiers
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`are found, because a spare time slot is available for processing when a state identifier is
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`not present.
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`A further aspect of the invention provides a distance calculation engine within a speech
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`recognition system. The distance calculation engine may be included within an
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`accelerator. The accelerator may include logic to interface with other parts of a speech
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`recognition circuit, in addition to the distance engine, although this is not essential. For
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`example, the accelerator may include one or more results memories for storing distances
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`calculated by the distance calculation engine. The accelerator may also include at least
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`one of a memory for storing one or more acoustic models, a decompressor for
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`decompressing acoustic data that has been stored in a compressed format, a memory for
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`storing feature vectors, a checksum or data signature calculation means, buffers for data
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`storage, and data registers. The accelerator may be implemented in software or in
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`hardware, or in a combination. It may be physically separate to the rest of the speech
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`recognition circuit, although this is not essential.
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`The distance calculation engine may calculate one or more of a wide range of distance
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`metrics and probability distributions. The distances may represent the likely
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`correspondance of feature vectors to states in an acoustic model. In other words, the
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`distances can indicate the similarity of an audio data frame to each possible state in an
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`acoustic model
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`There are a wide variety of probability distributions that can be used for the distance
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`calculation stage of a speech recogniser, and a wide variety of distance metrics used.
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`These are widely documented in the literature. A point is a simple example of a
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`probability distribution.
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`A common choice is to use Gaussian Distributions and correspondingly the
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`Mahalanobis Distance metric. The Gaussian probability distribution is then defined by a
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`mean vector, which defines centre point in the N-dimensional space, and a Covariance
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`matrix which defines the shape of the probability distribution. It is common to restrict
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`the Covariance matrix to be a diagonal matrix ( only N non-zero values along the
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`diagonal of the NxN matrix) which significantly lowers the implementation cost by
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`reducing the number of arithmetic operations.
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`In particular embodiments, the distance calculated is a Mahalanobis distance. Particular
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`examples of this are described later in the specification.
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`In one embodiment, the distance engine autonomously computes all of the distances
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`associated with a given feature vector. This may comprise computing distances for
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`every state in the lexicon. The distance engine may operate in a pipelined manner with
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`other stages of the recognition process. In this context a distance is an indication of the
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`probability or likelihood that a feature vector corresponds to a particular state. An
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`important class of distance computation in speech recognition is the calculation of
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`output state probabilities in recognisers using Hidden Markov Models. Another
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`possible use is in