Method and system for acoustic communication of data

Information

  • Patent Grant
  • 11683103
  • Patent Number
    11,683,103
  • Date Filed
    Friday, October 13, 2017
    6 years ago
  • Date Issued
    Tuesday, June 20, 2023
    a year ago
Abstract
The present invention relates to a method for receiving data transmitted acoustically. The method includes the steps of receiving an acoustically transmitted signal; and decoding the signal using, at least, a first plurality of voters to extract the data. The first plurality of voters comprise differing values for a first acoustic characteristic to address interference. A system and software are also disclosed.
Description

This application is the U.S. national phase of International Application No. PCT/GB2017/053113 filed Oct. 13, 2017 which designated the U.S. and claims priority to GB Patent Application No. 1617408.8 filed Oct. 13, 2016, the entire contents of each of which are hereby incorporated by reference.


FIELD OF INVENTION

The present invention is in the field of data communication. More particularly, but not exclusively, the present invention relates to a method and system for acoustic communication of data.


BACKGROUND

There are a number of solutions to communicating data wirelessly over a short range to and from devices. The most typical of these is WiFi. Other examples include Bluetooth and Zigbee.


An alternative solution for a short range data communication is described in U.S. Patent Publication Ser. No. 12/926,470, DATA COMMUNICATION SYSTEM. This system, invented by Patrick Bergel and Anthony Steed, involves the transmission of data using an audio signal transmitted from a speaker and received by a microphone. This system involves the encoding of data, such as shortcode, into a sequence of tones within the audio signal.


This acoustic communication of data provides for novel and interesting applications. However, acoustic communication of data does involve unique problems. Specifically, because the signals are transmitted acoustically, the receiver receives a signal that may include a lot of interference created by the environment in which the signal is transmitted which may, for example, be reverberation (including early/late reflections). At the point of receiving the audio, distortions caused by interference have the effect of reducing the reliable data rates due to the decoder's increased uncertainty about a signal's original specification. For example, early reflections which are coherent but delayed versions of the direct signal, usually created from an acoustic reflection from a hard surface, may make it more difficult for a decoder to confidently determine the precise start or end point of a signal feature/note. This decreases overall reliability. It is therefore preferable to reduce these effects at the receiver. Otherwise the data encoded within the signal can be difficult to accurately detect. This can result in non-communication of data in certain environments or under certain conditions within environments.


There is a desire to improve the acoustic communication of data.


It is an object of the present invention to provide a method and system for acoustic communication of data which overcomes the disadvantages of the prior art, or at least provides a useful alternative.


SUMMARY OF INVENTION

According to a first aspect of the invention there is provided a method for receiving data transmitted acoustically, including:


a) receiving an acoustically transmitted signal; and


b) decoding the signal using, at least, a first plurality of voters to extract the data;


wherein the first plurality of voters comprise differing values for a first acoustic characteristic to address interference.


The interference may be environmental interference.


The first acoustic characteristic may be one selected from the set of reverberation cancellation, timing offset, noise cancellation, and harmonics.


The environmental interference may be one or more of reverberation, reflections, echo, distortion, delay and noise.


The signal may be decoded using, at least, a second plurality of voters to extract the data, and wherein the second plurality of voters may comprise differing values for a second acoustic characteristic to address environmental interference. The second acoustic characteristic may be one selected from the set of FFT bins, timing offset, noise, and harmonics.


The first plurality of voters may be increased by one or more voters when the data cannot be successfully initially extracted.


The acoustically transmitted signal may be received at a first device. The signal may be decoded at the first device.


The first plurality of voters may further comprise differing values for a second acoustic characteristic to address environmental interference.


The signal may be decoded using, at least, a second plurality of voters, wherein the second plurality of voters may comprise differing values for an acoustic characteristic to address environmental interference.


The data may be encoded within the signal in accordance with an encoding format. The encoding format may include one or more of a header, error correction, and a payload. The error-correction may be Reed-Solomon. The encoding format may include encoding of data within the signal as a sequence of tones.


The signal may be decoded using a decoding method comprising:


Each voter reporting whether the encoding format is detected within the signal.


The decoding method may further comprise:


Using the error correction, selecting the voter which detects the least errors in the encoding format of the signal.


The decoding method may use a confidence interval for the voters.


Each of the voters may be pre-weighted.


The decoding method may further comprise:


Decoding the signal using consensus amongst the voters.


The decoding method may further comprise:


Decoding the signal using statistical information about the signal from at least some voters.


Other aspects of the invention are described within the claims.





BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the invention will now be described, by way of example only, with reference to the accompanying drawings in which:



FIG. 1: shows a block diagram illustrating a system in accordance with an embodiment of the invention;



FIG. 2: shows a flow diagram illustrating a method in accordance with an embodiment of the invention;



FIG. 2a: shows a diagram illustrating voters with different reverberation cancellation acoustic characteristics processing an audio signal in accordance with an embodiment of the invention;



FIG. 2b: shows a diagram illustrating voters with different timing offset acoustic characteristics processing an audio signal in accordance with an embodiment of the invention;



FIGs. 3A and 3B show a flow diagram illustrating a method in accordance with an embodiment of the invention; and



FIG. 4: shows a diagram illustrating an encoding format for an audio signal for use with a method in accordance with an embodiment of the invention.





DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

The present invention provides a method and system for the acoustic communication of data.


The inventors have discovered that the audio signal, when it is received, could be processed by a plurality of different decoding engines. Each engine can be configured with different assumptions about the acoustic characteristics of the environment in which the audio signal was acoustically transmitted. The outputs from engines (called voters by the inventors) can then be used to more effectively decode the signal to extract the data encoded in the signal.


In FIG. 1, a system 100 in accordance with an embodiment of the invention is shown.


A first device is shown 101. This device 101 may include a speaker 102. The device 101 may be configured to acoustically transmit a signal, for example, via the speaker 102.


A second device 103 is shown. This second device 103 may include or be connected to a microphone 104. The microphone 104 may be configured to receive signals acoustically transmitted, for example, by the first device 101, and to forward those signals to one or more processors 105 within the second device 103.


The microphone 104 and the processor(s) 105 may be connected via a communications bus or via a wired or wireless network connection.


The processor(s) 105 may be configured to decode the received signal using a plurality of voters to extract data within the signal. The voters may be configured with differing values for an acoustic characteristic to address interference. The processor(s) 105 may be configured to perform the method described in relation to FIG. 2.


It will be appreciated by those skilled in the art that the above embodiments of the invention may be deployed on different devices and in differing architectures.


Referring to FIG. 2, a method 200 for receiving acoustically transmitted data in accordance with an embodiment of the invention will be described.


In step 201, an acoustically transmitted signal is received (for example, via microphone 104). The signal encodes data. The data may be, for example, encoded as a sequence of tones. The encoding format of the signal may include a header, error correction and a payload, it may also include a checksum. The error correction component of the transmitted signal may be in a separate part of the transmitted signal or may be interleaved or otherwise contained within the payload section. An example of an encoding format will be described later in relation to FIG. 4. Reed-Solomon may be used as error correction as well as other forms such as Hamming or Turbo Codes, for example. At least a part of the encoding of the data and/or encoding format of the signal may be performed as described in U.S. patent Publication Ser. No. 12/926,470. The frequencies may be monophonic Frequency Shift Keying (FSK) or use a combination of frequencies to represent a data symbol similar to the DTMF encoding standard using Dual (or ‘n’) Tone Multiple Frequency Shift keying. The frequencies may be human audible or above the limit of human hearing (>20 kHz).


In step 202, the signal is decoded to extract data within the signal using a plurality of voters. The plurality of voters are configured within differing values for an acoustic characteristic to address interference (such as environmental interference). For example, the acoustic characteristic may be reverberation cancellation, timing offset, noise cancellation, or harmonics.


In examples where the acoustic characteristic is timing offset (e.g. where the environment creates interfering coherent, delayed versions of the direct signal), the values may be small artificial delays or advances in the relative positions of each voter with respect to the received input signal.


In examples where the acoustic characteristic is reverberation cancellation (e.g. where the environment creates reverberation interference), the values may be a reverb rolloff exponent (α) and/or a reverb cancellation magnitude (β), such that different voters will have different reverb rolloff exponent and reverb cancellation magnitude values. This is illustrated in FIG. 2a which shows voters 1, 2, and 3 with different reverberation cancellations attempting to detect a note (or tone) within a sequence of tones within the received audio signal.


The signal may be processed using a fast fourier transform (FFT) to produce bins of magnitudes across the spectrum. The FFT can be calculated on a per-frame basis. With the reverb cancellation values, the value passed to the decoder at a voter at a given frame t (Zt) is a combination of the current FFT magnitude (Xt) and a function of previous output values (Yt−1):

Yt=αYt−1+(1−α)Xt
Zt=Xt−βYt−1


Where the reverb cancellation is characterised by two parameters:

    • α∈[0, 1]: reverb rolloff exponent, which should be selected proportionally to the length of the reverb tail of the acoustic environment; Typically close to 1.
    • β∈[0, 1]: reverb cancellation magnitude, which determine the degree to which reverb is subtracted from the magnitude of the current spectral frame.


In examples where the acoustic characteristic is timing offset (e.g. where the environment causes reflection or delay interference), the values may be offset values such that different voters will have offsets of different magnitude to accommodate different delays. This is illustrated in FIG. 2b which shows voters A, B, and C attempt to decode the same audio signal with a sequence of tones with different timing offsets.


In some embodiments, the plurality of voters may be configured with one or more further acoustic characteristics which may differ. Each of the further acoustic characteristics may be configured for addressing interference (such as environmental interference).


In some embodiments, a second plurality of voters are also used to decode the signal, this set of voters may have one or more of the same values for the acoustic characteristic as voters within the first plurality of voters, but may have a second acoustic characteristic that differs between them.


In some embodiments, one or more additional voters are added to the first set of voters when data cannot be successfully extracted.


In some embodiments, different voters may be configured to listen for a plurality of different encoding formats. These formats may be different in schema e.g. note length, definitions of ‘frontdoor’, payload and error correction components. These formats may also be separated by frequency, (e.g. in separate bands with one occupying a frequency range above or below the others), or with the frequencies of their notes interleaved or otherwise combined within the same total frequency range.


Furthermore, and in some embodiments, within step 202, the signal may be decoded using a decoding method where each voter reports a measure of confidence in the decoded signal. This may correspond to metrics from the acoustic space (for example, distance measures between ideal tone frequencies and analysed tone frequencies), or from the digital line coding schema (for example, minimising the number of errors corrected within Forward Error Correction, and/or using a binary measure of data integrity such as a checksum or CRC code).


The data extracted in accordance with the decoding provided by the selected voter may be identified as the data encoded within the signal. In some embodiments, a consensus method across the voters may be used to identify the data. In some embodiments, each of the voters may be pre-weighted. Statistical information from at least some of the voters may be used to decode the signal to extract the data.


Referring to FIGS. 3A and 3B, a method and system in accordance with an embodiment of the invention will be described. In this embodiment, the audio signal will be termed a Chirp™ signal.


Voters are configured to differ with respect to their frame-offset, meaning the voters look at the timing of the signal differently from each other. This may enable the decoder as a whole to make a number of guesses regarding the actual start and end locations of each note (and the Chirp signal as a whole), thereby improving its detection accuracy by reducing the overlaps in detection between adjacent notes.


Typically the perceived timing of notes is altered due to the effects of reverb, making the addition of a de-reverberation step useful in conjunction with this timing offset.


Also the voters may apply reverb compensation differently (specifically different values of α & β as described in relation to FIG. 2)—this is particularly effective for tackling differences between different acoustic environments when where the Chirp signal is being played is not already known.


More generally, the voter characteristics may be tailored to be well suited in a variety of different acoustic conditions that decoders may face in real world scenarios. In embodiments, the voter system may not be optimised for one particular scenario, but made more robust to a very wide range of alterations caused by noise and acoustic effects during transmission.


In embodiments, this primarily is reverb cancellation, but could also include early/late reflections, room modes, echo, frequency dependent reverberation times, Doppler effects, background noise, harmonic distortion, adaptive filtering (to filter out any acoustic output of the decoding device), minimum confidence/magnitude thresholds for note detections (to have tolerant or intolerant voters), and others. Hardware characteristics could also be taken into account such as microphone and loudspeaker frequency responses.


For example, with respect to frequency dependent reverberation times each voter may have different expectations for reverberation decay rate at particular frequencies, these frequencies may correspond to frequencies that the encoder is expected to produce. The expected decay rate at each frequency then undergoes a reverberation cancellation process as described above.


It will be appreciated that different numbers of voters may be used. For example, the system may use five voters.


The number of voters may be selected based on the computation abilities of the processing device. It may also be adapted dynamically during operation based on the number of errors present during decoding. Additional voters with different parameters may be created if initial decoding with an existing voter set fails.



FIGS. 3A and 3B illustrate the application of the voters for each frame of audio.


a) Each voter receives the output of the FFT for each frame of audio


b) The voter applies different timing and reverb compensation to the input, and keeps its own ‘history’/rolling average of its own output to be applied in the next frame.


c) Each voter declares whether or not it thinks it has decoded a Chirp signal (based on thresholds which also vary between voters), and also how many errors it has corrected during the Reed-Solomon error correction phase. Other results besides number of errors may be used to judge the ‘quality’ of a decoding. These results may include the distance between expected and measured pitch of particular tones or acoustic energy of each tone. A measurement of quality may also take into account the timing and measured duration of a note at the receiver, since the timing at the sending device is known and can be compared. It will be appreciated that different parameters can be combined in this way to produce an aggregated ‘confidence’ parameter which in turn can be used to select a preferred voter or subset plurality of voters.


d) If any voters have detected a Chirp signal, the voter with the least number of errors corrected, or highest confidence/quality measure, is chosen and the audio engine declares a Chirp signal having been heard.


Alternative Embodiments

The embodiments described above in relation to FIGS. 3A and 3B operate almost exclusively in the frequency domain—that is, after performing an FFT on the input signal. However, alternative embodiments may perform per-voter signal processing specifically for dereverberation as described above separately before performing the FFT and subsequent peak detection. In one example the input signal still represented in the time-domain is split into multiple channels, the number being equal to the number of voters present. Each channel is then modified using standard Finite Impulse Response, or Infinite Impulse Response filters, or standard convolution methods to modify each channel's and each subsequent voter's input signal before frequency analysis. In this embodiment, each filter is configured such that it amplifies particular frequencies present in the encoded signal. In another embodiment, each filter is configured such that it attenuates particular frequencies not present in the encoded signal. The modification to the signal before the FFT may also include gain or dynamic compression.


In some embodiments, the number and configuration of each voter can be increased and optimised based on the expected range of acoustic environments that the encoder-decoder pair will work in (i.e. for an industrial application with static, known acoustic characteristics, the number of voters can be decreased; while for a consumer mobile app expected to be taken into a wide variety of different acoustic contexts the number (and variety) of voters (and their parameter ranges) can be increased).


Referring to FIG. 4, an encoding format will be described. This encoding format comprises a header 400 which includes “front door” start tones. These tones may be the same across all audio signals encoding data within the system and can assist a receiver to determine when an audio signal encodes data. The encoding format further comprises a payload 401 and forward error correction 402. It can be seen that this encoding format defines the header 400, payload 401 and forward error correction 402 as comprising a sequence of tones across a frequency spectrum. Preferably this frequency spectrum includes or comprises the human-audible frequency spectrum. The tones may be monophonic or polyphonic.


A potential advantage of some embodiments of the present invention is improved reliability of data transmission across different acoustics. For example, when an acoustic transmission solution is required to work across a range of unknown acoustic environments (e.g. train stations to living rooms), the provision of multiple voters, each responding differently increases reliability across this range. Furthermore, in some embodiments, each voter can be individually optimised for different acoustic scenarios—including extreme parameter ranges—without adversely affecting the overall voting outcome. Thus as long as the characteristics of each voter varies considerably, diminishing returns may be avoided as voters are increased (when looking across a wide range of acoustic contexts).


While the present invention has been illustrated by the description of the embodiments thereof, and while the embodiments have been described in considerable detail, it is not the intention of the applicant to restrict or in any way limit the scope of the appended claims to such detail. Additional advantages and modifications will readily appear to those skilled in the art. Therefore, the invention in its broader aspects is not limited to the specific details, representative apparatus and method, and illustrative examples shown and described. Accordingly, departures may be made from such details without departure from the spirit or scope of applicant's general inventive concept.

Claims
  • 1. A method for receiving data transmitted acoustically, including: receiving, via a microphone, an acoustically transmitted audio signal;pre-processing the received acoustically transmitted audio signal; anddecoding the pre-processed signal using a first plurality of voters, a second plurality of voters and a third plurality of voters to extract the data from the pre-processed signal, wherein the first plurality of voters comprise differing values for a first acoustic characteristic to address interference and each voter of the first plurality of voters is obtained based on processing the same pre-processed signal,wherein the second plurality of voters comprise differing values for a second acoustic characteristic to address environmental interference,wherein the third plurality of voters comprise differing values for a third acoustic characteristic to address environmental interference, andwherein the first acoustic characteristic comprising reverberation cancellation, the second acoustic characteristic comprising timing offset, and the third acoustic characteristic comprising harmonics.
  • 2. A method as claimed in claim 1, wherein the interference is environmental interference.
  • 3. A method as claimed in claim 1, wherein decoding the pre-processed signal includes decoding the pre-processed signal using a fourth plurality of voters to extract the data from the pre-processed signal, wherein the fourth plurality of voters comprise differing values for a fourth acoustic characteristic to address environmental interference, the fourth acoustic characteristic comprising noise cancellation.
  • 4. A method as claimed in claim 1, wherein the interference is environmental interference including one or more of reverberation, reflections, echo, distortion, delay and noise.
  • 5. A method as claimed in claim 1, wherein the first plurality of voters is increased by one or more voters when the data cannot be successfully initially extracted.
  • 6. A method as claimed in claim 1, wherein the acoustically transmitted signal is received at a first device comprising the microphone and the acoustically transmitted signal is transmitted by a speaker external to the first device.
  • 7. A method as claimed in claim 6, wherein the pre-processed signal is decoded at the first device.
  • 8. A method as claimed in claim 1, wherein the first plurality of voters further comprise differing values for another acoustic characteristic to address environmental interference.
  • 9. A method as claimed in claim 1, wherein a number of the plurality of voters used to extract the data from the pre-processed signal is dynamically adjusted based on an error present during the decoding.
  • 10. A method as claimed in claim 1, wherein the data is encoded within the acoustically transmitted signal in accordance with an encoding format.
  • 11. A method as claimed in claim 10, wherein the encoding format includes a header, error correction, and a payload.
  • 12. A method as claimed in claim 11, wherein the encoding format includes error correction and the error correction is Reed-Solomon.
  • 13. A method as claimed in claim 10, wherein the encoding format includes encoding of data within the acoustically transmitted signal as a sequence of tones.
  • 14. A method as claimed in claim 1, wherein the pre-processed signal is decoded using a decoding method comprising: each voter of the first plurality of voters reporting whether an encoding format is detected within the pre-processed signal.
  • 15. A method as claimed in claim 14, wherein the decoding method further comprises: using error correction, selecting the voter from the first plurality of voters which detects the least errors in the encoding format of the pre-processed signal.
  • 16. A method as claimed in claim 14, wherein the decoding method uses a confidence interval for the first plurality of voters.
  • 17. A method as claimed in claim 14, wherein each of the voters of the first plurality of voters are pre-weighted.
  • 18. A method as claimed in claim 14, wherein the decoding method further comprises: decoding the pre-processed signal using consensus amongst the first plurality of voters.
  • 19. A method as claimed in claim 14, wherein the decoding method further comprises: decoding the pre-processed signal based on statistical information about a measure of confidence of the decoded signal by least some voters of the first plurality of voters.
  • 20. An apparatus comprising: a microphone;memory; andone or more processors configured to: receive, via the microphone, an acoustically transmitted audio signal encoding data;pre-process the received acoustically transmitted audio signal; anddecode the pre-processed signal using a first plurality of voters, a second plurality of voters and a third plurality of voters to extract the data from the pre-processed signal,wherein the first plurality of voters comprise differing values for a first acoustic characteristic to address interference and each voter of the first plurality of voters is obtained based on processing the same pre-processed signal,wherein the second plurality of voters comprise differing values for a second acoustic characteristic to address environmental interference,wherein the third plurality of voters comprise differing values for a third acoustic characteristic to address environmental interference, andwherein the first acoustic characteristic comprising reverberation cancellation, the second acoustic characteristic comprising timing offset, and the third acoustic characteristic comprising harmonics.
  • 21. A system comprising: a first device comprising a speaker for acoustically transmitting an audio signal encoding data and one or more processors; anda second device comprising a microphone for acoustically receiving the audio signal and one or more processors configured to:receive, using the microphone, an acoustically transmitted audio signal;pre-process the received acoustically transmitted audio signal; anddecode the pre-processed signal using a first plurality of voters, a second plurality of voters and a third plurality of voters to extract the data from the pre-processed signal,wherein the first plurality of voters comprise differing values for a first acoustic characteristic to address interference and each voter of the first plurality of voters is obtained based on processing the same pre-processed signal,wherein the second plurality of voters comprise differing values for a second acoustic characteristic to address environmental interference,wherein the third plurality of voters comprise differing values for a third acoustic characteristic to address environmental interference, andwherein the first acoustic characteristic comprising reverberation cancellation, the second acoustic characteristic comprising timing offset, and the third acoustic characteristic comprising harmonics.
  • 22. A non-transitory computer readable medium configured for storing computer-readable instructions that, when executed on one or more processors, cause the one or more processors to: receive, via a microphone, an acoustically transmitted audio signal encoding data;pre-process the received acoustically transmitted audio signal; anddecode the pre-processed signal using a first plurality of voters, a second plurality of voters and a third plurality of voters to extract the data from the pre-processed signal,wherein the first plurality of voters comprise differing values for a first acoustic characteristic to address interference and each voter of the first plurality of voters is obtained based on processing the same pre-processed signal,wherein the second plurality of voters comprise differing values for a second acoustic characteristic to address environmental interference,wherein the third plurality of voters comprise differing values for a third acoustic characteristic to address environmental interference, andwherein the first acoustic characteristic comprising reverberation cancellation, the second acoustic characteristic comprising timing offset, and the third acoustic characteristic comprising harmonics.
  • 23. The apparatus of claim 20, wherein the first acoustic characteristic includes a reverb cancelation magnitude determining a degree to which reverb is subtracted from the magnitude of a current spectral frame.
  • 24. The apparatus of claim 20, wherein each voter of the first plurality of voters reports a measure of confidence in the data decoded from the pre-processed signal.
  • 25. The apparatus of claim 20, wherein a number of voters of the first plurality of voters used for decoding is dynamically adjusted during decoding based on a number of errors present during decoding.
  • 26. The apparatus of claim 20, wherein pre-processing the received acoustically transmitted audio signal includes obtaining a fast fourier transform of the received acoustically transmitted audio signal.
Priority Claims (1)
Number Date Country Kind
1617408 Oct 2016 GB national
PCT Information
Filing Document Filing Date Country Kind
PCT/GB2017/053113 10/13/2017 WO
Publishing Document Publishing Date Country Kind
WO2018/069731 4/19/2018 WO A
US Referenced Citations (126)
Number Name Date Kind
4045616 Sloane Aug 1977 A
4048074 Bruenemann et al. Sep 1977 A
4101885 Blum Jul 1978 A
4323881 Mori Apr 1982 A
4794601 Kikuchi Dec 1988 A
6133849 McConnell et al. Oct 2000 A
6163803 Watanabe Dec 2000 A
6532477 Tang et al. Mar 2003 B1
6711538 Omori et al. Mar 2004 B1
6766300 Laroche Jul 2004 B1
6909999 Thomas et al. Jun 2005 B2
6996532 Thomas Feb 2006 B2
7058726 Osaku et al. Jun 2006 B1
7349668 Ilan et al. Mar 2008 B2
7379901 Philyaw May 2008 B1
7403743 Welch Jul 2008 B2
7944847 Trine May 2011 B2
8494176 Suzuki et al. Jul 2013 B2
8594340 Takara et al. Nov 2013 B2
8782530 Beringer et al. Jul 2014 B2
9118401 Nieto et al. Aug 2015 B1
9137243 Suzuki et al. Sep 2015 B2
9237226 Frauenthal et al. Jan 2016 B2
9270811 Atlas Feb 2016 B1
9344802 Suzuki et al. May 2016 B2
10090003 Wang Oct 2018 B2
10186251 Mohammadi Jan 2019 B1
10236006 Gurijala et al. Mar 2019 B1
10236031 Gurijala Mar 2019 B1
20020107596 Thomas et al. Aug 2002 A1
20020152388 Linnartz et al. Oct 2002 A1
20020184010 Eriksson et al. Dec 2002 A1
20030065918 Willey Apr 2003 A1
20030195745 Zinser, Jr. et al. Oct 2003 A1
20030212549 Steentra et al. Nov 2003 A1
20040002858 Attias et al. Jan 2004 A1
20040081078 McKnight et al. Apr 2004 A1
20040133789 Gantman et al. Jul 2004 A1
20040148166 Zheng Jul 2004 A1
20040264713 Grzesek Dec 2004 A1
20050049732 Kanevsky et al. Mar 2005 A1
20050086602 Philyaw et al. Apr 2005 A1
20050219068 Jones et al. Oct 2005 A1
20060167841 Allan et al. Jul 2006 A1
20060253209 Hersbach et al. Nov 2006 A1
20060287004 Fuqua Dec 2006 A1
20070063027 Belfer et al. Mar 2007 A1
20070121918 Tischer May 2007 A1
20070144235 Werner et al. Jun 2007 A1
20070174052 Manjunath et al. Jul 2007 A1
20070192672 Bodin et al. Aug 2007 A1
20070192675 Bodin et al. Aug 2007 A1
20070232257 Otani et al. Oct 2007 A1
20080002882 Voloshynovskyy et al. Jan 2008 A1
20080011825 Giordano et al. Jan 2008 A1
20080027722 Haulick et al. Jan 2008 A1
20080031315 Ramirez et al. Feb 2008 A1
20080059157 Fukuda et al. Mar 2008 A1
20080112885 Okunev et al. May 2008 A1
20080144624 Marcondes et al. Jun 2008 A1
20080232603 Soulodre Sep 2008 A1
20080242357 White Oct 2008 A1
20080262928 Michaelis Oct 2008 A1
20090034712 Grasley et al. Feb 2009 A1
20090119110 Oh et al. May 2009 A1
20090123002 Karthik et al. May 2009 A1
20090141890 Steenstra et al. Jun 2009 A1
20090254485 Baentsch et al. Oct 2009 A1
20100030838 Atsmon et al. Feb 2010 A1
20100064132 Ravikiran Sureshbabu Mar 2010 A1
20100088390 Bai et al. Apr 2010 A1
20100134278 Srinivasan et al. Jun 2010 A1
20100146115 Bezos Jun 2010 A1
20100223138 Dragt Sep 2010 A1
20100267340 Lee Oct 2010 A1
20100290641 Steele Nov 2010 A1
20110173208 Vogel Jul 2011 A1
20110276333 Wang et al. Nov 2011 A1
20110277023 Meylemans et al. Nov 2011 A1
20110307787 Smith Dec 2011 A1
20120045994 Koh et al. Feb 2012 A1
20120084131 Bergel et al. Apr 2012 A1
20120214416 Kent et al. Aug 2012 A1
20120214544 Shivappa et al. Aug 2012 A1
20130010979 Takara et al. Jan 2013 A1
20130030800 Tracey et al. Jan 2013 A1
20130034243 Yermeche et al. Feb 2013 A1
20130077798 Otani et al. Mar 2013 A1
20130113558 Pfaffinger et al. May 2013 A1
20130216058 Furuta et al. Aug 2013 A1
20130223279 Tinnakornsrisuphap et al. Aug 2013 A1
20130275126 Lee Oct 2013 A1
20140028818 Brockway, III et al. Jan 2014 A1
20140046464 Reimann Feb 2014 A1
20140053281 Benoit et al. Feb 2014 A1
20140074469 Zhidkov Mar 2014 A1
20140108020 Sharma et al. Apr 2014 A1
20140142958 Sharma et al. May 2014 A1
20140164629 Barth et al. Jun 2014 A1
20140172141 Mangold Jun 2014 A1
20140172429 Butcher et al. Jun 2014 A1
20140258110 Davis et al. Sep 2014 A1
20150004935 Fu Jan 2015 A1
20150088495 Jeong et al. Mar 2015 A1
20150141005 Suryavanshi et al. May 2015 A1
20150215299 Burch et al. Jul 2015 A1
20150248879 Miskimen et al. Sep 2015 A1
20150271676 Shin et al. Sep 2015 A1
20150349841 Mani et al. Dec 2015 A1
20150371529 Dolecki Dec 2015 A1
20150382198 Kashef et al. Dec 2015 A1
20160007116 Holman Jan 2016 A1
20160098989 Layton et al. Apr 2016 A1
20160358619 Ramprashad Dec 2016 A1
20170208170 Mani et al. Jul 2017 A1
20170279542 Knauer et al. Sep 2017 A1
20180106897 Shouldice et al. Apr 2018 A1
20180115844 Lu et al. Apr 2018 A1
20180213322 Napoli et al. Jul 2018 A1
20180359560 Defraene et al. Dec 2018 A1
20190045301 Family et al. Feb 2019 A1
20190096398 Sereshki Mar 2019 A1
20200091963 Christoph et al. Mar 2020 A1
20200105128 Frank Apr 2020 A1
20200169327 Lin et al. May 2020 A1
20210098008 Nesfield et al. Apr 2021 A1
Foreign Referenced Citations (29)
Number Date Country
103259563 Aug 2013 CN
105790852 Jul 2016 CN
106921650 Jul 2017 CN
1760693 Mar 2007 EP
2334111 Jun 2011 EP
2916554 Sep 2015 EP
3275117 Jan 2018 EP
3408936 Dec 2018 EP
3526912 Aug 2019 EP
2369995 Jun 2002 GB
2484140 Apr 2012 GB
H1078928 Mar 1998 JP
2001320337 Nov 2001 JP
2004512765 Apr 2004 JP
2004139525 May 2004 JP
2007121626 May 2007 JP
2007195105 Aug 2007 JP
2008219909 Sep 2008 JP
0016497 Mar 2000 WO
0115021 Mar 2001 WO
0150665 Jul 2001 WO
0161987 Aug 2001 WO
0163397 Aug 2001 WO
0211123 Feb 2002 WO
0235747 May 2002 WO
2004002103 Dec 2003 WO
2005006566 Jan 2005 WO
2008131181 Oct 2008 WO
2016094687 Jun 2016 WO
Non-Patent Literature Citations (82)
Entry
International Search Report for PCT/GB2017/053113 dated Jan. 18, 2018, 4 pages.
Written Opinion of the ISA for PCT/GB2017/053113 dated Jan. 18, 2018, 7 pages.
Wang, Avery Li-Chun. An Industrial-Strength Audio Search Algorithm. Oct. 27, 2003, 7 pages, [online], [retrieved on May 12, 2020] Retrieved from the Internet URL: https://www.researchgate.net/publication/220723446_An_Industrial_Strength_Audio_Search_Algorithm.
Advisory Action dated Mar. 1, 2022, issued in connection with U.S. Appl. No. 16/342,078, filed Apr. 15, 2019, 3 pages.
European Patent Office, European EPC Article 94.3 dated Oct. 8, 2021, issued in connection with European Application No. 17790809.2, 9 pages.
European Patent Office, European EPC Article 94.3 dated Dec. 10, 2021, issued in connection with European Application No. 18845403.7, 41 pages.
European Patent Office, European EPC Article 94.3 dated Oct. 12, 2021, issued in connection with European Application No. 17795004.5, 8 pages.
European Patent Office, European EPC Article 94.3 dated Oct. 28, 2021, issued in connection with European Application No. 18752180.2, 7 pages.
Final Office Action dated Mar. 18, 2022, issued in connection with U.S. Appl. No. 16/623,160, filed Dec. 16, 2019, 14 pages.
Non-Final Office Action dated Oct. 15, 2021, issued in connection with U.S. Appl. No. 16/496,685, filed Sep. 23, 2019, 12 pages.
Non-Final Office Action dated Dec. 27, 2021, issued in connection with U.S. Appl. No. 16/956,905, filed Jun. 22, 2020, 12 pages.
Notice of Allowance dated Feb. 18, 2022, issued in connection with U.S. Appl. No. 16/564,766, filed Sep. 9, 2019, 8 pages.
United Kingdom Patent Office, United Kingdom Examination Report dated Oct. 8, 2021, issued in connection with United Kingdom Application No. GB2113511.6, 7 pages.
United Kingdom Patent Office, United Kingdom Examination Report dated Oct. 29, 2021, issued in connection with United Kingdom Application No. GB1709583.7, 3 pages.
United Kingdom Patent Office, United Kingdom Office Action dated Mar. 24, 2022, issued in connection with United Kingdom Application No. GB2202914.4, 3 pages.
United Kingdom Patent Office, United Kingdom Office Action dated Jan. 28, 2022, issued in connection with United Kingdom Application No. GB2113511.6, 3 pages.
United Kingdom Patent Office, United Kingdom Office Action dated Feb. 9, 2022, issued in connection with United Kingdom Application No. GB2117607.8, 3 pages.
United Kingdom Patent Office, United Kingdom Search Report dated Sep. 22, 2021, issued in connection with United Kingdom Application No. GB2109212.7, 5 pages.
Bourguet et al. “A Robust Audio Feature Extraction Algorithm for Music Identification,” AES Convention 129; Nov. 4, 2010, 7 pages.
C. Beaugeant and H. Taddei, “Quality and computation load reduction achieved by applying smart transcoding between CELP speech codecs,” 2007, 2007 15th European Signal Processing Conference, pp. 1372-1376.
European Patent Office, Decision to Refuse dated Nov. 13, 2019, issued in connection with European Patent Application No. 11773522.5, 52 pages.
European Patent Office, European Extended Search Report dated Aug. 31, 2020, issued in connection with European Application No. 20153173.8, 8 pages.
European Patent Office, Summons to Attend Oral Proceedings mailed on Mar. 15, 2019, issued in connection with European Application No. 11773522.5-1217, 10 pages.
Final Office Action dated Oct. 16, 2014, issued in connection with U.S. Appl. No. 12/926,470, filed Nov. 19, 2010, 22 pages.
Final Office Action dated Aug. 17, 2017, issued in connection with U.S. Appl. No. 12/926,470, filed Nov. 19, 2010, 22 pages.
Final Office Action dated Nov. 30, 2015, issued in connection with U.S. Appl. No. 12/926,470, filed Nov. 19, 2010, 25 pages.
Final Office Action dated Apr. 20, 2020, issued in connection with U.S. Appl. No. 16/012,167, filed Jun. 19, 2018, 21 pages.
Gerasimov et al. “Things That Talk: Using sound for device-to-device and device-to-human communication”, Feb. 2000 IBM Systems Journal 39(3.4):530-546, 18 pages. [Retrieved Online] URlhttps://www.researchgate.net/publication/224101904_Things_that_talk_Using_sound_for_device-to-device_and_device-to-human_communication.
Glover et al. “Real-time detection of musical onsets with linear prediction and sinusoidal modeling.”, 2011 EURASIP Journal on Advances in Signal Processing 2011, 68, Retrieved from the Internet URL: https://doi.org/10.1186/1687-6180-2011-68, Sep. 20, 2011, 13 pages.
Gomez et al: “Distant talking robust speech recognition using late reflection components of room impulse response”, Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on, IEEE, Piscataway, NJ, USA, Mar. 31, 2008, XP031251618, ISBN: 978-1-4244-1483-3, pp. 1581-4584.
Gomez et al., “Robust Speech Recognition in Reverberant Environment by Optimizing Multi-band Spectral Subtraction”, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP, Jan. 1, 2008, 6 pages.
Goodrich et al., Using Audio inn Secure Device Pairing, International Journal of Security and Networks, vol. 4, No. 1.2, Jan. 1, 2009, p. 57, Inderscience Enterprises Ltd., 12 pages.
International Bureau, International Preliminary Report on Patentability and Written Opinion, dated Apr. 16, 2019, issued in connection with International Application No. PCT/GB2017/053112, filed on Oct. 13, 2017, 12 pages.
International Bureau, International Preliminary Report on Patentability and Written Opinion, dated Apr. 16, 2019, issued in connection with International Application No. PCT/GB2017/053113, filed on Oct. 13, 2017, 8 pages.
International Bureau, International Preliminary Report on Patentability and Written Opinion, dated Dec. 17, 2019, issued in connection with International Application No. PCT/GB2018/051645, filed on Jun. 14, 2018, 7 pages.
International Bureau, International Preliminary Report on Patentability and Written Opinion, dated Mar. 19, 2019, issued in connection with International Application No. PCT/GB2017/052787, filed on Sep. 19, 2017, 7 pages.
International Bureau, International Preliminary Report on Patentability and Written Opinion, dated Jun. 23, 2020, issued in connection with International Application No. PCT/GB2018/053733, filed on Dec. 20, 2018, 7 pages.
International Bureau, International Preliminary Report on Patentability and Written Opinion, dated Sep. 24, 2019, issued in connection with International Application No. PCT/GB2018/050779, filed on Mar. 23, 2018, 6 pages.
International Bureau, International Search Report and Written Opinion dated Apr. 11, 2019, issued in connection with International Application No. PCT/GB2018/053733, filed on Dec. 20, 2018, 10 pages.
International Bureau, International Search Report and Written Opinion dated Oct. 4, 2018, issued in connection with International Application No. PCT/GB2018/051645, filed on Jun. 14, 2018, 14 pages.
International Searching Authority, International Search Report and Written Opinion dated Mar. 13, 2018, issued in connection with International Application No. PCT/GB2017/053112, filed on Oct. 13, 2017, 18 pages.
International Searching Authority, International Search Report and Written Opinion dated Nov. 29, 2017, in connection with International Application No. PCT/GB2017/052787, 10 pages.
International Searching Authority, International Search Report and Written Opinion dated Nov. 30, 2011, in connection with International Application No. PCT/GB2011/051862, 6 pages.
International Searching Authority, International Search Report dated Jun. 19, 2018, issued in connection with International Application No. PCT/GB2018/050779, filed on Mar. 23, 2018, 8 pages.
Japanese Patent Office, Office Action dated Jun. 23, 2015, issued in connection with JP Application No. 2013-530801, 8 pages.
Japanese Patent Office, Office Action dated Apr. 4, 2017, issued in connection with JP Application No. 2013-530801, 8 pages.
Japanese Patent Office, Office Action dated Jul. 5, 2016, issued in connection with JP Application No. 2013-530801, 8 pages.
Lopes et al. “Acoustic Modems for Ubiquitous Computing”, IEEE Pervasive Computing, Mobile and Ubiquitous Systems. vol. 2, No. 3 Jul.-Sep. 2003, pp. 62-71. [Retrieved Online] URL https://www.researchgate.net/publication/3436996_Acoustic_modems_for_ubiquitous_computing.
Madhavapeddy, Anil. Audio Networking for Ubiquitous Computing, Oct. 24, 2003, 11 pages.
Madhavapeddy et al., Audio Networking: The Forgotten Wireless Technology, IEEE CS and IEEE ComSoc, Pervasive Computing, Jul.-Sep. 2005, pp. 55-60.
Madhavapeddy et al., Context-Aware Computing with Sound, University of Cambridge 2003, pp. 315-332.
Monaghan et al. “A method to enhance the use of interaural time differences for cochlear implants in reverberant environments.”, published Aug. 17, 2016, Journal of the Acoustical Society of America, 140, pp. 1116-1129. Retrieved from the Internet URL: https://asa.scitation.org/doi/10.1121/1.4960572 Year: 2016, 15 pages.
Non-Final Office Action dated Mar. 25, 2015, issued in connection with U.S. Appl. No. 12/926,470, filed Nov. 19, 2010, 24 pages.
Non-Final Office Action dated Mar. 28, 2016, issued in connection with U.S. Appl. No. 12/926,470, filed Nov. 19, 2010, 26 pages.
Non-Final Office Action dated Jan. 6, 2017, issued in connection with U.S. Appl. No. 12/926,470, filed Nov. 19, 2010, 22 pages.
Non-Final Office Action dated Aug. 9, 2019, issued in connection with U.S. Appl. No. 16/012,167, filed Jun. 19, 2018, 15 pages.
Non-Final Office Action dated Feb. 5, 2014, issued in connection with U.S. Appl. No. 12/926,470, filed Nov. 19, 2010, 22 pages.
Non-Final Office Action dated Aug. 12, 2021, issued in connection with U.S. Appl. No. 16/342,060, filed Apr. 15, 2019, 88 pages.
Non-Final Office Action dated Sep. 24, 2020, issued in connection with U.S. Appl. No. 16/012,167, filed Jun. 19, 2018, 20 pages.
Non-Final Office Action dated Jan. 29, 2021, issued in connection with U.S. Appl. No. 16/342,060, filed Apr. 15, 2019, 59 pages.
Non-Final Office Action dated Sep. 7, 2021, issued in connection with U.S. Appl. No. 16/623,160, filed Dec. 16, 2019, 11 pages.
Notice of Allowance dated Mar. 15, 2018, issued in connection with U.S. Appl. No. 12/926,470, filed Nov. 19, 2010, 10 pages.
Notice of Allowance dated Mar. 19, 2021, issued in connection with U.S. Appl. No. 16/012,167, filed Jun. 19, 2018, 9 pages.
Soriente et al., “HAPADEP: Human-Assisted Pure Audio Device Pairing*” Computer Science Department, University of California Irvine, 12 pages. [Retrieved Online] URLhttps://www.researchgate.net/publication/220905534_HAPADEP_Human-assisted_pure_audio_device_pairing.
Tarr, E.W. “Processing perceptually important temporal and spectral characteristics of speech”, 2013, Available from ProQuest Dissertations and Theses Professional. Retrieved from https://dialog.proquest.com/professional/docview/1647737151?accountid=131444, 200 pages.
United Kingdom Patent Office, United Kingdom Examination Report dated Jun. 11, 2021, issued in connection with United Kingdom Application No. GB1716909.5, 5 pages.
United Kingdom Patent Office, United Kingdom Examination Report dated Feb. 2, 2021, issued in connection with United Kingdom Application No. GB1715134.1, 5 pages.
United Kingdom Patent Office, United Kingdom Office Action dated Jan. 22, 2021, issued in connection with United Kingdom Application No. GB1906696.8, 2 pages.
Advisory Action dated Aug. 19, 2022, issued in connection with U.S. Appl. No. 16/496,685, filed Sep. 23, 2019, 3 pages.
European Patent Office, European EPC Article 94.3 dated Jul. 6, 2022, issued in connection with European Application No. 20153173.8, 4 pages.
Final Office Action dated May 10, 2022, issued in connection with U.S. Appl. No. 16/496,685, filed Sep. 23, 2019, 15 pages.
International Bureau, International Search Report and Written Opinion dated Sep. 21, 2022, issued in connection with International Application No. PCT/US2022/072465, filed May 20, 2022, 32 pages.
International Searching Authority, International Search Repod and Written Opinion dated Jan. 5, 2022, issued in connection with International Application No. PCT/US2021/048380, filed Aug. 31, 2021, 15 pages.
Non-Final Office Action dated Oct. 4, 2022, issued in connection with U.S. Appl. No. 16/496,685, filed Sep. 23, 2019, 15 pages.
Non-Final Office Action dated Jul. 1, 2022, issued in connection with U.S. Appl. No. 16/623,160, filed Dec. 16, 2019, 10 pages.
Non-Final Office Action dated Jul. 11, 2022, issued in connection with U.S. Appl. No. 17/660,185, filed Apr. 21, 2022, 20 pages.
Non-Final Office Action dated Jul. 21, 2022, issued in connection with U.S. Appl. No. 16/956,905, filed Jun. 22, 2020, 15 pages.
Non-Final Office Action dated Feb. 5, 2021, issued in connection with U.S. Appl. No. 16/342,078, filed Apr. 15, 2019, 13 pages.
Notice of Allowance dated Aug. 11, 2022, issued in connection with U.S. Appl. No. 16/342,078, filed Apr. 15, 2019, 15 pages.
Notice of Allowance dated Mar. 29, 2022, issued in connection with U.S. Appl. No. 16/342,060, filed Apr. 15, 2019, 24 pages.
Notice of Allowance dated Apr. 5, 2022, issued in connection with U.S. Appl. No. 16/956,905, filed Jun. 22, 2020, 9 pages.
United Kingdom Patent Office, United Kingdom Office Action dated May 10, 2022, issued in connection with United Kingdom Application No. GB2202914.4, 5 pages.
Related Publications (1)
Number Date Country
20190253154 A1 Aug 2019 US