DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1, 2, 4, 7-12, 14-16, 23 and 24 are rejected under 35 U.S.C. 103 as being unpatentable over LaBosco et al. (US 20200265859 A1; hereafter LaBosco) in view of McCowan et al. (US 20200154200 A1; hereafter McCowan).
Regarding claims 1, 4 and 9, LaBosco discloses (in Figs. 4, 8 and 10) a method of reducing echo in an audio system (400) comprising a microphone (any one of 104a-104d), an acoustic echo canceller (AEC) (112), and one or more processors (e.g., [0215]), the method comprising, using any of the one or more processors:
assigning locations (beam#) of an environment (see 904 in Fig. 10) to location-based AEC parameters (predetermined h in Fig. 4) based on location values for the locations (each assigned beam is directed toward a specific location of the environment, the specific location inherently has a location value to distinguish one location from the other location in the environment);
storing location-based AEC parameters in a memory (414 stores parameter h0(k)-hn-1(k); those parameters represent location-based AEC parameters; see Fig. 8 and 10, more explanation provided below) in communication with the one or more processors;
receiving (by inputs of 106) an audio signal detected by the microphone (any one of 104a-104d), the audio signal produced by an audio source (e.g., a person at near end of the microphone) located in the audio pick-up region of the microphone (a general microphone can pick up sound in its surrounding; thus reads on the area within the audio pickup range of the microphone);
generating an audio localization of the detected audio signal (by the combination of 402 and 406);
determining (by 406), based on the audio localization, location representing a first location of the audio source relative to the microphone (the location of the person talks at the moment);
deploying a microphone lobe towards the first location associated with the audio signal (output of 408 representing audio pickup by a microphone lobe towards the location of the person talks at the moment);
obtaining, from the memory (414), one or more AEC parameters (representing impulse ha, see upper right corner of Fig. 4) of the location-based AEC parameters based on the first location (h0-hn-1 are location-based AEC parameters), wherein obtaining the one or more AEC parameters comprises:
identifying (reads on the inherent functionality of the processor locating the library in the memory storing the AEC parameters), from the memory (414), a group of location points located within the audio pick-up region (the predetermined impulse filter coefficients are predetermined for the corresponding location points), and
retrieving, from the memory (414), the one or more AEC parameters corresponding to a subset of the location-based AEC parameters stored in association with the first location point (e.g., h0(k) associated with the first location point and is being retrieved, h0(k) is a subset of location-based AEC parameters among all location-based AEC parameters stored in 414; the definition of subset: a set each of whose elements is an element of an inclusive set; see https://www.merriam-webster.com/dictionary/subset; based on the definition of subset, the claimed subset broadly reads on one element or one determined beam position or one predetermined AEC parameter associated with a corresponding location point);
initializing the AEC (412 in 112) using the one or more AEC parameters (e.g., h0(k)); and
generating an echo-cancelled output signal (y(n)) using the initialized AEC (e.g., h0(k)) for filter (412) and based on the detected audio signal (output of 408) and a reference signal (204) provided to the AEC (112) ([0227]).
LaBosco does not explicitly show generating a map of an environment and assigning map locations of the map to location-based AEC parameters based on location coordinate values for the map locations. As shown in Figs. 8 and 10, the location-based AEC parameters representing AEC parameters for specific locations, that are audio-pick-up regions in an environment, are assigned and stored in a memory with index values. In LaBosco, the index value represents locations of the environment, so index value broadly read on location value. In a different embodiment, LaBosco teaches that the beam position could be represented by coordinates ([0195]). Thus, instead of index value or in addition to index value, the beam position could be represented by location coordinate value without generating any unexpected effect.
Although Fig. 10 of LaBosco illustrate an view of a room, it is unclear whether such view is visually presented to the user when the location-based AEC parameters are assigned and stored. In the same field of endeavor, McCowan teaches an user interface that allows an user to visualize the precise beam locations in environment and storing parameters for the beams (e.g., [0007]-[0009]). A map is a visual or symbolic representation of an area (map definition - Google Search). Thus, McCowan teaches generating a map of an environment comprising an audio-pick-up region of the microphone. A circle on the interface (map) symbolizes the beam location. Thus, the circle is a map location of the map. A general graphic user interface taught in McCowan is an electronic device that converts machine-readable coordinates, while the user defines a point on the interface, to a visual representation (such as the location of a cursor, or a circle in McCowan). Thus, McCowan teaches generating a map, assigning map locations of the map to location-based beam parameters based on location coordinate values for the map locations, and storing location-based beam parameters in a memory in communication with one or more processor.
The interface taught in McCowan would have motivated one skilled in the art to improve LaBosco’s system. LaBosco teaches that the library of AEC coefficients are trained based on each beam angle (712 in Fig. 7, [0241]). LaBosco further shows a hypothetical environment in Fig. 10, which includes audio pick-up region, which illustrates mapping of a plurality of beam areas in an environment where one beam area is clearly located behind another beam area with the table at the center of the environment (e.g., 906k is behind 906b). McCowan teaches providing an user interface that generates a map of an environment comprising audio pick-up region (e.g., regions or beamzones in Figs. 1A, 1B and 2) for detecting voice and providing echo cancellation for a conference room ([0052]). By providing a map of the environment, the engineer who designs the teleconferencing system could visualize the position of each participant relative to each other and with respect to the microphones (Fig. 9) and the direction of corresponding beam; wherein the visualized position could be identified (such as Beam #15 and Beam #2 in Fig. 10 in LaBosco, and index value in Fig. 8). Although LaBosco illustrates that each microphone beam covers an area which occupies by a corresponding sound source (such as a talker in a conference), the beam inherently has a center point which provides the strongest and the most sensitive point for sound capturing. Identifying a beam by its center point would provide a precise location point for the best sound capturing. One skilled in the art would have been motivated to direct the beam to the actual point occupied by the sound source in space, not a general area, for training the location-based AEC parameter. Each beam position is identified by a corresponding code in LaBosco (Fig. 8). Thus, it would have been obvious to one of ordinary skill in the art to modify LaBosco in view of McCowan by, during training, generating a map mapping sound sources into a plurality location points in the environment, directing a beam for a particular location point occupied by a sound source, determining the corresponding location-based AEC parameters for the respective map locations of the map, and storing the trained location-based AEC parameters in a memory in order to visually assigned beam location for each source in the environment (such as illustrated in Fig. 10) based on location coordinate values for the map locations and accurately determining AEC coefficients for the corresponding BF location points based on location coordinates in coordination with determining location-based AEC coefficient for the convergence of AEC for the BF location point and be able to retrieving the stored location-based AEC parameter when the BF is directed to the correspond location point based on the determined location coordinates.
LaBosco does not show location coordinates representing a first location for the embodiment as shown in Fig. 4. In a different embodiment, LaBosco teaches that the current beam position could be represented by coordinates or angle ([0195]). One skilled in the art would have recognized that they are functionally equivalent. Thus, it would have been obvious to one of ordinary skill in the art to modify Fig. 4 of LaBosco by encoding the current beam position using one of the well known representation, such as coordinates as taught in another embodiment, because it is considered as a matter of design preference to use a specific type of representation among several well known functionally equivalent types.
LaBosco does not show determining a first location point (e.g., Beam #15 in Fig. 10) from the group of location points (e.g., Beam #1-Beam#16 in Fig. 10) that is closest to the first location for the embodiment as shown in Fig. 4. As illustrated in Fig. 4, “ha” is selected from a library ([0026], [0226]). However, in a different embodiment, LaBosco teaches that the number of AEC parameter sets, predetermined and stored in a memory ([0182]), for a group of location points (e.g., 4 stored positions) could be less than the number of beam positions (e.g., 8 beam positions with one beam position reads on the claimed “first location”). The AEC controller (114) selects an AEC parameter set for a predetermined beam position that is closest to the current beam position determined by the beamformer ([0182], [0223]). Thus, it would have been obvious to one of ordinary skill in the art to modify embodiment of Fig. 4 of LaBosco by selecting a set of AEC parameter predetermined for a beam position from the memory that is closest to the actual beam position determined by the beamformer in order to efficiently cancel the echo without storing AEC parameters for each possible beamforming position in the environment.
Regarding claim 7, LaBosco teaches that the at-least one or more AEC parameters correspond to a second microphone lobe previously deployed towards the first location point (this reads on the scenario that the memory includes a set of parameter that is predetermined by a microphone lobe pointed at the same location of the current sound source).
Regarding claims 2 and 8, LaBosco fails to explicitly show determining a convergence status of AEC. However, when performing training ([0241]), the final set of AEC parameters for the predetermined beam angle should be the set that could cancel echo with a reasonable success. That is, AEC parameters are being adapted during training until AEC parameters would reach optimal values. One skilled in the art would have expected that the final set of AEC is a set indicating convergence of AEC filter and as stated in paragraph [0229]. See also the definition of convergence as provided in paragraph [0225]. Thus, it would have been obvious to one of ordinary skill in the art to modify LaBosco by determining the convergence state of AEC filter using the corresponding set of AEC parameters in order to store the best AEC parameters for the predetermined beam angle during training.
Regarding claims 10 and 11, LaBosco teaches the far end signal (204 in Fig. 4), the subtraction (410) and the remote computing device (through the path to 122 in Fig. 1).
Regarding claim 23, LaBosco fails to explicitly show 3-D location coordinates. However, LaBosco teaches a general xy coordinates defining a specific steering direction ([(0195]). One skilled in the art would have expected that any well known coordinate system could be used without generating any unexpected result. McCowan teaches utilizing spherical coordinates representing the defined locations in a space for steering beam by the beamformer ([0033]). Fig. 2 of McCowan shows an user interface that allowing the user visualizing the locations of beam (this is the explicit teaching of generating a map of an environment comprising an audio pick-up region of the microphone as discussed above with respect to claim 1). Fig. 9 of LaBosco illustrates the beam positions at different heights. Thus, it would have been obvious to one of ordinary skill in the art to further modify LaBosco and McCowan by utilizing a specific coordinate system, such as spherical coordinates as taught in McCowan, because it is considered as a matter of design preference to use a specific coordinate system for identifying a location in 3D space.
Claims 12, 14-16 and 24 correspond to claims 1, 7, 8, 10, 11 and 23 discussed above.
Claims 1-4, 7-12, 14-16, 23 and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Buck et al. (US 20140307883 A1; hereafter Buck) in view of LaBosco and McCowan.
Regarding claims 1 and 9, Buck discloses a method of reducing echo in an audio system comprising a microphone (101), an acoustic echo canceller (AEC) (107), and one or more processors, the method comprising, using any of the one or more processors:
generating location-based AEC parameters (“provided sets of filter coefficients”) for respective locations ([0072]);
storing the location-based AEC parameters in a memory (409 in Fig. 4 during initializing) in communication with the one or more processors (AEC filter parameters for a predetermined number of steering direction stored in memory; see [0072], [0106], [140], [0142], Figs. 4 and 5);
receiving (by 105) an audio signal detected by the microphone (101), the audio signal produced by an audio source (e.g., 103) located in the audio pick-up region (the look direction of the microphone 101 and BF 106) of the microphone (one or more microphones 101 is intended to pick-up audio from one or more sound sources at least in front of the one or more microphones 101 as illustrated in Fig. 1);
generating an audio localization of the audio signal (“A speaker localization module 105 is used to determine the position and/or the direction of arrival, in particular the position or direction of a speaker 103” in [0125]);
determining, based on the audio localization, location coordinates representing a first location of the audio source relative to the microphone ([0041]);
deploying (by 106) a microphone lobe (104) towards the first location associated with the detected audio signal (the location detected by the lobe, e.g., the speaker at 10 o’clock as shown in Fig. 1, [0125]);
obtaining (by 108), from the memory (109), one or more AEC parameters of the location-based AEC parameters based on the first location (the stored AEC parameters for the corresponding steering direction; [0126], [0152], [0072], [0106], [0140]), wherein obtaining the one or more AEC parameters comprises:
identifying (inherent function of processor for locating the area in the memory that stores “provided filter coefficients”), from the memory (109), a group of location points located within the audio pick-up region (a group of points with corresponding predetermined steering directions, [0016], e.g.), each location point associated with a previously-deployed microphone lobe (predetermined steering direction),
determining a first location point from the group of location points (to find a set of parameters in the memory as the best match), and
retrieving, from the memory (109), the one or more AEC parameters (the AEC parameter to be sent to 107) corresponding to a subset of the location-based AEC parameters stored in association with the first location point (e.g., the AEC parameter associated with steering direction to 10 o’clock and is being retrieved, this parameter is a subset of location-based AEC parameter among all location-based AEC parameters stored in 109; the definition of subset: a set each of whose elements is an element of an inclusive set; see https://www.merriam-webster.com/dictionary/subset; based on the definition of subset, the claimed subset broadly reads on one element or one determined beam position or one predetermined AEC parameter associated with a corresponding location point);
initializing the AEC using the one or more AEC parameters (sent the retrieved one or more AEC parameter from 109 to 107) as filter coefficients (for 107); and
generating an echo-cancelled output signal using the initialized AEC and based on the detected audio signal and a reference signal provided to the AEC (output of the subtractor using the initialized AEC and based on the detected audio signal and a reference signal provided to the AEC).
Buck does not explicitly show generating a map of an environment and assigning map locations of the map to location-based AEC parameters based on location coordinate values for the map locations. As illustrated in Fig. 1 of Buck, two sound sources are located at two different distinct location points in the environment. LaBosco shows another similar environment in Fig. 10, which includes audio pick-up region, which illustrates mapping of a plurality of beam areas in an environment where one beam area is clearly located behind another beam area with the table at the center of the environment (e.g., 906k is behind 906b). McCowan teaches an user interface that allows an user to visualize the precise beam locations in environment and storing parameters for the beams (e.g., [0007]-[0009]). A map is a visual or symbolic representation of an area (map definition - Google Search). Thus, McCowan teaches generating a map of an environment comprising an audio-pick-up region of the microphone. A circle on the interface (map) symbolizes the beam location. Thus, the circle is a map location of the map. A general graphic user interface taught in McCowan is an electronic device that converts machine-readable coordinates, while the user defines a point on the interface, to a visual representation (such as the location of a cursor, or a circle in McCowan). Thus, McCowan teaches generating a map, assigning map locations of the map to location-based beam parameters based on location coordinate values for the map locations, and storing location-based beam parameters in a memory in communication with one or more processor.
The interface taught in McCowan would have motivated one skilled in the art to improve Buck’s system. Buck teaches that a library of AEC coefficients are trained based on each beam angle (409 in Fig. 4 during initializing, see also [0072], [0106], [0140], [0142], Figs. 4 and 5). LaBosco teaches a hypothetical environment in Fig. 10, which includes audio pick-up region, which illustrates mapping of a plurality of beam areas in an environment where one beam area is clearly located behind another beam area with the table at the center of the environment (e.g., 906k is behind 906b). McCowan teaches providing an user interface that generates a map of an environment comprising audio pick-up region (e.g., regions or beamzones in Figs. 1A, 1B and 2) for detecting voice and providing echo cancellation for a conference room ([0052]). By providing a map of the environment, the engineer who designs the teleconferencing system could visualize the position of each participant relative to each other and with respect to the microphones (Fig. 9) and the direction of corresponding beam; wherein the visualized position could be identified (such as Beam #15 and Beam #2 in Fig. 10 in LaBosco, and index value in Fig. 8). Although LaBosco illustrates that each microphone beam covers an area which occupies by a corresponding sound source (such as a talker in a conference), the beam inherently has a center point which provides the strongest and the most sensitive point for sound capturing. Identifying a beam by its center point would provide a precise location point for the best sound capturing. One skilled in the art would have been motivated to direct the beam to the actual point occupied by the sound source in space, not a general area, for training the location-based AEC parameter. Each beam position is identified by a corresponding code in LaBosco (Fig. 8). Thus, it would have been obvious to one of ordinary skill in the art to modify Buck in view of LaBosco and McCowan by, during training, generating a map mapping sound sources into a plurality location points in the environment, directing a beam for a particular location point occupied by a sound source, determining the corresponding location-based AEC parameters for the respective map locations of the map based on location coordinate values for the map locations, and storing the trained location-based AEC parameters in a memory in order to visually helping assigning determining coefficient for the BF location point based on location coordinate values for the map location in coordination with determining AEC coefficient for the convergence of AEC for the BF location point and be able to retrieving the stored the AEC coefficient when the BF is directed to the corresponding location point based on the determined location coordinates.
Buck fails to explicitly show determining a first location point from the group of location points that is closest to the first location. However, such action is inherently performed as the retrieved one or more AEC coefficient is not randomly selected/retrieved. One skilled in the art would have expected, for example, the retrieved one or more AEC parameters for the source at 10 o’clock in Buck would be the subset that is closer to the source at 10 o’clock than the other subset for another source at 8 o'clock position. In another example, if only one sound source is present at 10 o’clock position and the memory of Buck includes one subset of AEC parameters for source at exactly 10 o’clock position and another subset of parameters for source at exactly 8 o’clock position, one skilled in the art would have expected that the retrieved subset of parameters would be the one for 10 o’clock position because the retrieved subset is the best match, aka., the closest position to the sound source. LaBosco is cited here to show the teaching more explicitly. Similar to Buck, LaBosco teaches a combination of beamformer and AEC for detecting voices from plural sound sources and providing echo cancellation (Figs. 7, 9 and 10). One skilled in the art would have recognized the similarity between the circuit in Buck and the one in LaBosco. While Buck is absent, in terms of words, on determining a first location point from the group of location points that is closest to the first location, LaBosco teaches selected the stored set of AEC parameters at a position that is closest to the current beam position ([0182], [0223]). When utilizing the stored set of AEC parameters that is closest to the current beam position, not only the adaptation of AEC parameters would be faster and more efficient so would the quality of echo being cancelled. Thus, it would have been obvious to one of ordinary skill in the art to modify Buck in view of LaBosco by retrieving one or more AEC coefficients from the memory representing a location that is closest to the first location (e.g., person at 10 o'clock position as shown in Fig. 1) in order to speed up the process of correctly estimating the echo by AEC.
Buck fails to show generating a map of the environment, the map comprising a plurality of location points (which are points within the audio pick-up region); and generating and storing in a memory the location-based AEC parameter in association with corresponding map locations. As illustrated in Fig. 1 of Buck, two sound sources are located at two different distinct location points in the environment. LaBosco shows another similar environment in Fig. 10, which includes audio pick-up region, which illustrates a mapping of a plurality of beam areas in an environment where one beam area is clearly located behind another beam area with the table at the center of the environment (e.g., 906k is behind 906b). McCowan teaches providing an user interface that generates a map of an environment comprising audio pick-up region (e.g., regions or beamzones in Figs. 1A, 1B and 2) for detecting voice and providing echo cancellation for a conference room ([0052]). By providing a map of the environment, the engineer who designs the teleconferencing system could visualize the position of each participant relative to each other and with respect to the microphones (Fig. 9) and the direction of corresponding beam. Although LaBosco illustrates that each microphone beam covers an area which occupies by a corresponding sound source (such as a talker in a conference), the beam inherently has a center point which provides the strongest and the most sensitive point for sound capturing. Identifying a beam by its center point would provide a precise location point for the best sound capturing. One skilled in the art would have been motivated to direct the beam to the actual point occupied by the sound source in space, not a general area. Each beam position is identified by a corresponding code in LaBosco (Fig. 8). Referring back to Buck, the steering direction could be specified by coordinates ([0041]). Thus, it would have been obvious to one of ordinary skill in the art to modify Buck in view of LaBosco and McCowan by generating a map mapping sound sources into a plurality location points in the environment, directing a beam for a particular location point occupied by a sound source, determining the corresponding AEC coefficient with convergence of the AEC and saving the determined AEC in association with the corresponding location point represented by location coordinates in a memory in order to accurately determining coefficient for the BF location point based on location coordinates in coordination with determining AEC coefficient for the convergence of AEC for the BF location point and be able to retrieving the stored the AEC coefficient when the BF is directed to the corresponding location point based on the determined location coordinates.
Regarding claim 2, the combination of Buck and LaBosco meets the claimed features. Buck teaches (Figs. 4 and 5)
receiving, a plurality of AEC parameters, each AEC parameter associated with convergence of the AEC for a select one of a plurality of microphone lobes (step 525, for the coefficient that meets “the quality of echo compensation” as discussed [0112], it is a coefficient associated with convergence of the AEC);
receiving location information for each of the plurality of microphone lobes (the location information as defined by 522, “the provided steering direction” in [0142] is at 10 o’clock position, e.g.), the location information identifying a location point from the group of location points that corresponds to the respective microphone lobe (e.g., the location information for the current steering direction at step 522 is for position at 10 o'clock, another location information for a new current steering direction at 8 o’clock when the processing loop returns to step 522);
storing (526, [0142]), in a database included in the memory (109), each of the plurality of AEC parameters in association with the corresponding location information,
wherein obtaining the one or more AEC parameters comprises: retrieving the one or more AEC parameters from the database based on the first location being closest to
the first location point (the combination of Buck and LaBosco as discussed above with respect to claim 1).
Regarding claim 3, Buck teaches: storing, in the database, a convergence timestamp in association with each AEC parameter ([0093], [0148], [0168], [0170]).
Regarding claim 4, the combination of Buck, LaBosco and McCowan teaches the claimed assigning (region # in McCowan, Beam # in LaBosco) and storing ([0072] in McCowan, [0241] in LaBosco, e.g.).
Regarding claim 7, Buck teaches that the at-least one or more AEC parameters correspond to a second microphone lobe previously deployed towards the first location point (this reads on the scenario that the memory includes a set of parameter that is predetermined by a microphone lobe pointed at the same location of the current sound source).
Regarding claim 8, Buck teaches that the AEC coefficient stored is the one that is proven to provide convergence of the AEC during adaptation. The claimed “determining ... convergence status of the AEC” reads on the state when the adaptation of the AEC coefficient has been finalized and be ready to be stored in the memory (Fig. 5 of Buck, [0142]).
Regarding claim 10, Buck teaches
receiving a far end audio signal (x(n) in Fig. 2) from a remote computing device (not explicitly shown, but inherently included) in communication with the audio system (through 210);
providing the far end audio signal (x(n)) to a loudspeaker (102) included in the audio system for playback;
providing the far end audio signal (x(n)) to the AEC (207) as the reference signal for estimating the echo (
D
^
) in the audio signal detected by the microphone (201); and
providing the echo-cancelled output signal (E) to the remote computing device.
Regarding claim 11, Buck shows generating the echo-cancelled output signal comprises: calculating an echo estimation signal (
D
^
) based on the reference signal (x(n)), and subtracting the echo estimation signal from the detected audio signal.
Regarding claim 23, Buck fails to explicitly show 3-D location coordinates. However, Buck teaches a general three parameters defining a specific steering direction ([0041]). One skilled in the art would have expected that any well known coordinate system could be used without generating any unexpected result. McCowan teaches utilizing spherical coordinates representing the defined locations in a space for steering beam by the beamformer ([0033]). Thus, it would have been obvious to one of ordinary skill in the art to further modify the combination of Buck, LaBosco and McCowan by utilizing a specific coordinate system, such as spherical coordinates as taught in McCowan, because it is considered as a matter of design preference to use a specific coordinate system for identifying a location in 3D space.
Claims 12, 14-16 and 24 corresponds to claims 1, 7, 8, 10, 11 and 23 discussed above.
Response to Arguments
Applicant's arguments filed 3/16/2026 have been fully considered but they are not persuasive.
On p. 10, applicant argued that none of cited references show “assigning map locations of the map to location-based AEC parameters based on location coordinate values for the map locations”. The office disagrees. McCowan teaches a visual representation of an environment where plural microphone beams would be directed to distinct locations. The visual representation of the environment in McCowan reads on claimed map. Furthermore, each circle shown in the user interface of McCowan is the location of the beam. The circle location as visualized by the user is defined by or based on machine readable location coordinate value. Thus, McCowan teaches assigning map locations of the map to location-based beam parameters based on location coordinate values for the map location. LaBosco teaches predetermined AEC parameters, stored in a memory, for several locations in an environment (Figs. 8 and 10). Using a graphic user interface, the user would be able to visualize the precision location of each location in the environment that requires AEC parameters. Thus, using a graphic user interface could speed up the process for assigning and/or providing a better echo cancellation coverage to be assigned to each and every required zones (such as a zone for each participant, or a zone for two participants). Thus, the combination of LaBosco and McCowan teaches the claimed features.
For the same reason as discussed above, the combination of Buck, LaBosco and McCowan teaches the claimed features.
Allowable Subject Matter
Claims 17, 18 and 20-22 are allowable over the prior art in the record.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PING LEE whose telephone number is (571)272-7522. The examiner can normally be reached Monday-Friday.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vivian Chin can be reached at 571-272-7848. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/PING LEE/ Primary Examiner, Art Unit 2695
Prosecution Insights