Source: http://www.google.com/patents/US7363227?ie=ISO-8859-1&dq=7565338
Timestamp: 2014-07-14 14:03:37
Document Index: 194636571

Matched Legal Cases: ['Application No. 60', 'Application No. 60', 'Application No. 60', 'Application No. 60', 'Application No. 60', 'Application No. 60']

Patent US7363227 - Disruption of speech understanding by adding a privacy sound thereto - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign in<nobr>Advanced Patent Search</nobr>PatentsA privacy apparatus adds a privacy sound into the environment, thereby confusing listeners as to which of the sounds is the real source. The privacy sound may be based on the speaker's own voice or may be based on another voice. At least one characteristic of the speaker (such as a characteristic of...http://www.google.com/patents/US7363227?utm_source=gb-gplus-sharePatent US7363227 - Disruption of speech understanding by adding a privacy sound theretoAdvanced Patent SearchPublication numberUS7363227 B2Publication typeGrantApplication numberUS 11/588,979Publication dateApr 22, 2008Filing dateOct 27, 2006Priority dateJan 10, 2005Fee statusLapsedAlso published asUS20070203698Publication number11588979, 588979, US 7363227 B2, US 7363227B2, US-B2-7363227, US7363227 B2, US7363227B2InventorsDaniel Mapes-Riordan, Jeffrey Specht, William DeKruifOriginal AssigneeHerman Miller, Inc.Export CitationBiBTeX, EndNote, RefManPatent Citations (22), Referenced by (9), Classifications (7), Legal Events (4) External Links: USPTO, USPTO Assignment, EspacenetDisruption of speech understanding by adding a privacy sound theretoUS 7363227 B2Abstract A privacy apparatus adds a privacy sound into the environment, thereby confusing listeners as to which of the sounds is the real source. The privacy sound may be based on the speaker's own voice or may be based on another voice. At least one characteristic of the speaker (such as a characteristic of the speaker's speech) may be identified. The characteristic may then be used to access a database of the speaker's own voice or another's voice, and to form one or more voice streams to form the privacy sound. The privacy sound may thus permit disruption of the ability to understand the source speech of the user by eliminating segregation cues that the auditory system uses to interpret speech.
RELATED APPLICATIONS This application is a continuation-in-part of U.S. patent application Ser. No. 11/326,269 filed on Jan. 4, 2006, which claims the benefit of U.S. Provisional Application No. 60/642,865, filed Jan. 10, 2005, the benefit of U.S. Provisional Application No. 60/684,141, filed May 24, 2005, and the benefit of U.S. Provisional Application No. 60/731,100, filed Oct. 29, 2005. U.S. patent application Ser. No. 11/326,269, U.S. Provisional Application No. 60/642,865, U.S. Provisional Application No. 60/684,141, and U.S. Provisional Application No. 60/731,100 are hereby incorporated by reference herein in their entirety.
FIELD The present application relates to a method and apparatus for disrupting speech and more specifically, a method and apparatus for disrupting speech from a single talker or multiple talkers.
BACKGROUND Office environments have become less private. Speech generated from a talker in one part of the office often travels to a listener in another part of the office. The clearly heard speech often distracts the listener, potentially lowering the listener's productivity. This is especially problematic when the subject matter of the speech is sensitive, such as patient information or financial information.
There have been attempts to combat the noise problem. The typical solution is to mask or cover-up the noise problem with �white� or �pink� noise. White noise is a random noise that contains an equal amount of energy per frequency band. Pink noise is noise having higher energy in the low frequencies. However, masking or covering-up the speech in the workplace is either ineffective (because the volume is too low) or overly distracting (because the volume must be very high to disrupt speech). Thus, the current solutions to solve the noise problem in the workplace are of limited effectiveness.
BRIEF SUMMARY A system and method for disrupting speech of a talker at a listener in an environment is provided. The system and method comprise determining a speech database, selecting a subset of the speech database, forming at least one speech stream from the subset of the speech database, and outputting at least one speech stream.
BRIEF DESCRIPTION OF THE DRAWINGS The foregoing and other objects, features and advantages of the invention will be apparent from the following more particular description of preferred embodiments of the invention, as illustrated in the accompanying drawings in which like reference characters refer to the same parts throughout the different views. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the invention. Moreover, in the figures, like referenced numerals designate corresponding parts throughout the different views.
DETAILED DESCRIPTION A privacy apparatus is provided that adds a privacy sound into the environment that may closely match the characteristics of the source (such as the one or more persons speaking), thereby confusing listeners as to which of the sounds is the real source. The privacy apparatus may be based on a talker's own voice or may be based on other voices. This permits disruption of the ability to understand the source speech of the talker by eliminating segregation cues that humans use to interpret human speech. The privacy apparatus reduces or minimizes segregation cues. The privacy apparatus may be quieter than random-noise maskers and may be more easily accepted by people.
A sound can overcome a target sound by adding a sufficient amount of energy to the overall signal reaching the ear to block the target sound from effectively stimulating the ear. The sound can also overcome cues that permit the human auditory system segregate the sources of different sounds without necessarily being louder than the target sounds. A common phenomenon of the ability to segregate sounds is known as the �cocktail party effect.� This effect refers to the ability of people to listen to other conversations in a room with many different people speaking. The means by which people are able to segregate different voices will be described later.
As shown at block 110, the speech fragment database is determined. The database may comprise any type of memory device (such as temporary memory (e.g., RAM) or more permanent memory (e.g., hard disk, EEPROM, thumb drive)). As discussed below, the database may be resident locally (such as a memory connected to a computing device) or remotely (such as a database resident on a network). The speech fragment database may contain any form that represents speech, such as an electronic form of .wav file that, when used to generate electrical signals, may drive a loudspeaker to generate sounds of speech. The speech that is stored in the database may be generated based on a human being (such as person speaking into a microphone) or may be simulated (such as a computer simulating speech to create �speech-like� sounds). Further, the database may include speech for a single person (such as the talker whose speech is sought to be disrupted) or may include speech from a plurality of people (such as the talker and his/her coworkers, and/or third-parties whose speech represents a cross-section of society).
As shown at block 220, the speech fragments are selected based on the talker input. For input comprising the talker's voice, the speech fragments may comprise phonemes, diphones, and/or syllables from the talker's own voice. Or, the system may analyze the talker's voice, and analyze various characteristics of the voice (such as fundamental frequency, formant frequencies, etc.) to select the optimum set of speech fragments. In a server based system, the server may perform the analysis of the optimum set of voices, compile the voice streams, generate a file (such as an MP3 file), and download the file to play on the local device. In this manner, the intelligence of the system (in terms of selecting the optimum set of speech fragments and generating the voice streams) may be resident on the server, and the local device may be responsible only for outputting the speech streams (e.g., playing the MP3 file). For input comprising attributes of the talker, the attributes may be used to select a set of speech fragments. For example, in an internet-based system, the talker may send via the internet to a server his or her attributes or actual speech recordings. The server may then access a database containing multiple sets of speech fragments (e.g., one set of speech fragments for a male age 15-20; a second set of speech fragments for female age 15-20; a third set of speech fragments for male age 20-25; etc.), and select a subset of the speech fragments in the database based on talker attributes (e.g., if the talker attribute is �male,� the server may select each set of speech fragments that are tagged as �male�).
As discussed above, the system may be for a single user or for multiple users. In a multi-user system, the speech fragment database may include speech fragments for a plurality of users. The database may be resident locally on the system (as part of a standalone system) or may be a network database (as part of a distributed system). A modified speech fragment database 300 for multiple users is depicted in FIG. 3. As shown, there are several sets of speech fragments. Correlated with each speech fragment is a user identification (ID). For example, User ID1, may be a number and/or set of characters identifying �John Doe.� Thus, the speech fragments for a specific user may be stored and tagged for later use.
As shown at block 810, the spectral energy content is measured. The measurement of the spectral energy content, such as the high frequency content in the speech, may help identify talkers who have significance sibilance (�sss�) in their speech. One way to measure this is to compute the ratio of high frequency to total frequency energy during unvoiced (no f0) portions of the speech.
As shown at block 816, the optimum set of voices is selected. One method of choosing an optimum set of voices from the speech database is to determine the number of separate talkers in the environment and to measure and keep track of their individual characteristics. In this scenario, it is assumed that individual voices characteristics can be separated. This may be possible for talkers with widely different speech parameters (e.g., male and female). Another method for choosing an optimum voice set is taking the speech input as one �global voice� without regard for individual talker characteristics and determining the speech parameters. This analysis of a �global voice,� even if more than one talker is present, may simplify processing.
During the creation of the speech database, such as the database depicted in FIG. 4, a range of sample speech is collected such that the desired range and resolution of the important speech parameters are adequately represented in the database. This process may include measuring voice privacy performance with systematic speech parameter variations. A correlation analysis of this data may be performed on this data using voice privacy performance (dB SPL needed to achieve confidential privacy) as the dependent variable and differences between the source talkers' speech parameters and the �disrupter� speech parameters (i.e., Δf0, Δf1, Δf2, Δf3, ΔVTL, Δfhigh, etc.) as the independent variables. This analysis yields the relative importance of each speech parameter in determining overall voice privacy performance.
Referring to FIG. 9, there is shown a flow diagram 900 for selecting speech fragments with single or multiple users. The measured speech parameters used to compute Δf0, Δf1, Δf2, Δf3, ΔVTL, Δhigh, etc. may be based on the mean values of their respective parameters. In the case of multiple voices, a search may first be made to determine the number of peaks in the f0 distribution, as shown at block 902. Each peak in the f0 distribution may represent an individual voice. As shown in block 904, it is determined if the number of peaks is greater than 1. If so, then it is determined that multiple talkers are present. If not, it is determined that a single talker is present. If a single talker is present, �x� of the best voices for each peak are determined. �x� may be equal to 4 voices, or may be less or greater than 4 voices. The determination of the optimum voices may be as described above. For multiple talkers, a predetermined number of voices, such as �y� voices may be determined for each peak. Since generating a great number of voices may tend to towards white noise, a maximum number of voices may be determined. For example, the maximum number of voices may be 12 voices, however fewer or greater numbers of maximum voices may be used. Thus, for a maximum of 12 voices, for 2-3 peaks (translating into identifying 2 or 3 talkers), four voices may be generated for each peak. For 4 peaks, three voices per peak may be generated. For 5 voices, 2 of the most prominent peaks will use 3 voices and the remainder may use 2 voices. For 6 voices, 2 voices per peak may be used. This process is dynamic in that it adjusts as peaks change through time. The numbers provided are merely for illustrative purposes.
Further, there may be 1, 2, or �N� loudspeakers. The loudspeakers may contain two loudspeaker drivers positioned 120 degrees off axis from each other so that each loudspeaker can provide 180 degrees of coverage. Each driver may receive separate signals. The number of total loudspeakers systems needed may be dependent on the listening environment in which it is placed. For example, some closed conference rooms may only need one loudspeaker system mounted outside the door in order to provide voice privacy. By contrast, a large, open conference area may need six or more loudspeakers to provide voice privacy.
Patent CitationsCited PatentFiling datePublication dateApplicantTitleUS3541258May 29, 1967Nov 17, 1970Sylvania Electric ProdConference communication system with independent variable amplification of sidetone and conferee signalsUS3718765Feb 18, 1970Feb 27, 1973Halaby JCommunication system with provision for concealing intelligence signals with noise signalsUS3879578Jun 18, 1973Apr 22, 1975Wildi TheodoreSound masking method and systemUS4068094Feb 24, 1976Jan 10, 1978Gretag AktiengesellschaftMethod and apparatus for the scrambled transmission of spoken information via a telephony channelUS4099027Jan 2, 1976Jul 4, 1978General Electric CompanySpeech scramblerUS4195202Jan 3, 1978Mar 25, 1980Technical Communications CorporationVoice privacy system with amplitude maskingUS4232194Mar 16, 1979Nov 4, 1980Ocean Technology, Inc.Voice encryption systemUS4438526Apr 26, 1982Mar 20, 1984Conwed CorporationAutomatic volume and frequency controlled sound masking systemUS4852170Dec 18, 1986Jul 25, 1989R & D AssociatesReal time computer speech recognition systemUS4905278Jul 20, 1988Feb 27, 1990British Broadcasting CorporationScrambling of analogue electrical signalsUS5036542Nov 2, 1989Jul 30, 1991Kehoe Brian DAudio surveillance discouragement apparatus and methodUS5355430 *Aug 12, 1991Oct 11, 1994Mechatronics Holding AgMethod for encoding and decoding a human speech signal by using a set of parametersUS5781640Jun 7, 1995Jul 14, 1998Nicolino, Jr.; Sam J.System for suppressing the undesirable effects of a noise sourceUS6188771Mar 10, 1999Feb 13, 2001Acentech, Inc.Personal sound masking systemUS6888945Feb 9, 2001May 3, 2005Acentech, Inc.Personal sound masking systemUS7143028Jul 24, 2002Nov 28, 2006Applied Minds, Inc.Method and system for masking speechUS20030091199Oct 24, 2002May 15, 2003Horrall Thomas R.Sound masking systemUS20040019479Jul 24, 2002Jan 29, 2004Hillis W. DanielMethod and system for masking speechUS20040125922Sep 10, 2003Jul 1, 2004Specht Jeffrey L.Communications device with sound masking systemUS20050065778 *Sep 24, 2003Mar 24, 2005Mastrianni Steven J.Secure speechUS20060009969Jun 22, 2004Jan 12, 2006Soft Db Inc.Auto-adjusting sound masking system and methodUS20060109983Feb 15, 2005May 25, 2006Young Randall KSignal masking and method thereof* Cited by examinerReferenced byCiting PatentFiling datePublication dateApplicantTitleUS8050931 *Mar 19, 2008Nov 1, 2011Yamaha CorporationSound masking system and masking sound generation methodUS8140326 *Jun 6, 2008Mar 20, 2012Fuji Xerox Co., Ltd.Systems and methods for reducing speech intelligibility while preserving environmental soundsUS8271288 *Sep 22, 2011Sep 18, 2012Yamaha CorporationSound masking system and masking sound generation methodUS8670986 *Mar 6, 2013Mar 11, 2014Medical Privacy Solutions, LlcMethod and apparatus for masking speech in a private environmentUS20090171670 *Mar 28, 2008Jul 2, 2009Apple Inc.Systems and methods for altering speech during cellular phone useUS20110182438 *Jan 25, 2011Jul 28, 2011Yamaha CorporationMasker sound generation apparatus and programUS20120166188 *Dec 28, 2010Jun 28, 2012International Business Machines CorporationSelective noise filtering on voice communicationsUS20130185061 *Mar 6, 2013Jul 18, 2013Medical Privacy Solutions, LlcMethod and apparatus for masking speech in a private environmentWO2014055866A1 *Oct 4, 2013Apr 10, 2014Medical Privacy Solutions, LlcMethods and apparatus for masking speech in a private environment* Cited by examinerClassifications U.S. Classification704/273, 704/E21.019International ClassificationG10L21/00Cooperative ClassificationH04K1/10, G10L21/06European ClassificationG10L21/06, H04K1/10Legal EventsDateCodeEventDescriptionJun 12, 2012FPExpired due to failure to pay maintenance feeEffective date: 20120422Apr 22, 2012LAPSLapse for failure to pay maintenance feesDec 5, 2011REMIMaintenance fee reminder mailedJun 18, 2007ASAssignmentOwner name: HERMAN MILLER, INC., MICHIGANFree format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:MAPES-RIORDAN, DANIEL;SPECHT, JEFFREY;ELI, SUSAN (LEGAL REPRESENTATIVE OF THE ESTATE OF WILLIAM DEKRUIF);REEL/FRAME:019449/0585;SIGNING DATES FROM 20070102 TO 20070409RotateOriginal ImageGoogle Home - Sitemap - USPTO Bulk Downloads - Privacy Policy - Terms of Service - About Google Patents - Send FeedbackData provided by IFI CLAIMS Patent Services©2012 Google