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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 17 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 17 recites the limitation " The one or more non-transitory computer-readable media of claim 1". There is insufficient antecedent basis for this limitation in the claim. Claim 1, from which claim 17 depends, is directed towards a computer implemented method and makes no recitation of “one or more non-transitory computer-readable media” so it is unclear which “one or more non-transitory computer-readable media” are being referred to. Therefore claim 17 is unclear and thus indefinite. It is the examiner’s interpretation that claim 17 is intended to be dependent upon claim 14.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-9, 12, 14-16, and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhou et al. ("BatMapper: Acoustic sensing based indoor floor plan construction using smartphones." Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services. 2017., “Zhou”) in view of Dokmanic et al. (US 20140180629 A1, “Dokmanic”).
Regarding claim 1, Zhou discloses a computer-implemented method for estimating a room layout, the method comprising: receiving a plurality of candidate wall distance estimates for a plurality of walls in an acoustic environment and a plurality of confidence scores, each confidence score of the plurality of confidence scores associated with a different candidate wall distance estimate of the plurality of candidate wall distance estimates; receiving device location data for a plurality of audio processing devices in the acoustic environment; determining, based on the device location data, a location of each wall in the plurality of walls relative to each audio processing device in the plurality of audio processing devices([pg. 4], for each emitted chirp, multiple peaks corresponding to different echoes are detected. Using a threshold, only the top-K strongest peaks are selected. Top 6 peaks are chosen for the top microphone, and top 10 peaks are chosen for the bottom microphone)([pg. 5], echo candidates are generated for both microphones and a probabilistic evidence accumulation method is conducted for each candidate. Candidates with the greatest probabilities are then used to determine path length to walls.)(it is the examiner’s interpretation that the path length for a given microphone to a wall implicitly includes the microphone (or device) location);
Zhou may not explicitly teach generating a room layout matrix that includes the plurality of candidate wall distance estimates, wherein each row of the room layout matrix is associated with a respective audio processing device of the plurality of audio processing devices and each column is associated with a respective wall of the plurality of walls, and wherein each of the candidate wall distance estimates is associated with the respective walls based on the plurality of confidence scores; determining, based on a highest confidence score in each column of the room layout matrix and the location data, a set of wall distance estimates from an ordinal audio processing device selected from the plurality of audio processing devices; and determining, based on the set of wall distance estimates, one or more room layout estimates of the acoustic environment.
Dokmanic teaches generating a room layout matrix that includes the plurality of candidate wall distance estimates, wherein each row of the room layout matrix is associated with a respective audio processing device of the plurality of audio processing devices and each column is associated with a respective wall of the plurality of walls, and wherein each of the candidate wall distance estimates is associated with the respective walls based on the plurality of confidence scores; determining, based on a highest confidence score in each column of the room layout matrix and the location data, a set of wall distance estimates from an ordinal audio processing device selected from the plurality of audio processing devices; and determining, based on the set of wall distance estimates, one or more room layout estimates of the acoustic environment(Fig. 3, [0073]-[0082], a 4 microphone array is situated in a 2D room and a loudspeaker is set up at an arbitrary position. If the image source and microphone positions are known, then the room geometry can be reconstructed. If the loudspeaker fires a pulse, each microphone picks up echoes for all of the walls and generates a Euclidean distance matrix. In order to know which peaks in an impulse response corresponds to each wall, point sets in Euclidean spaces are used and echoes associated with particular walls are ranked. In two dimensions, the ranks go up to 4. The Euclidean distance matrix is comprised of multiple TDOA for the microphones. If the matrix properties verify the rank positioning of the walls, then the selected echoes correspond to a wall)).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art of acoustic floorplan reconstruction, before the effective filing date of the claimed invention, to modify the method of Zhou, to include the room layout matrix wall localization of Dokmanic with a reasonable expectation of success, with the motivation of reconstructing the geometry of the room using the locations of the microphones and the speaker to determine the location in which first order reflections reflect off of the walls [0073]-[0082].
Regarding claim 2, Zhou, as modified in view of Dokmanic teaches the method of claim 1. Zhou further discloses the one or more room layout estimates of the acoustic environment includes at least one of a length, a width, a height, or a volume of the acoustic environment ([pg. 5], distances of candidates with highest probability will be used to infer path lengths, thus corridor geometry such as length).
Regarding claim 3, Zhou, as modified in view of Dokmanic teaches the method of claim 2. Dokmanic teaches the length of the acoustic environment is a sum of a distance of a front wall of the acoustic environment from the ordinal audio processing device and a distance of a back wall of the acoustic environment from the ordinal audio processing device ([0079]-[0082], If the loudspeaker fires a pulse, each microphone picks up echoes for all of the walls. If the distances between the image sources and the microphones are known, it is possible to reconstruct the locations of the image sources and the 2-D room geometry based on the first order reflections. In order to know which peaks in an impulse response corresponds to each wall, point sets in Euclidean spaces are used and echoes associated with particular walls are ranked. In two dimensions, the ranks go up to 4.)(it is the examiner’s interpretation that the length of the acoustic environment would implicitly be the sum of distances to opposite walls with respect to an ordinal audio processing device).
Regarding claim 4, Zhou, as modified in view of Dokmanic teaches the method of claim 2. Dokmanic further teaches the width of the acoustic environment is a sum of a distance of a left wall of the acoustic environment from the ordinal audio processing device and a distance of a right wall of the acoustic environment from the ordinal audio processing device([0079]-[0082], If the loudspeaker fires a pulse, each microphone picks up echoes for all of the walls. If the distances between the image sources and the microphones are known, it is possible to reconstruct the locations of the image sources and the 2-D room geometry based on the first order reflections. In order to know which peaks in an impulse response corresponds to each wall, point sets in Euclidean spaces are used and echoes associated with particular walls are ranked. In two dimensions, the ranks go up to 4.)(it is the examiner’s interpretation that the length of the acoustic environment would implicitly be the sum of distances to opposite walls with respect to an ordinal audio processing device) (it is the examiner’s interpretation that the width of the acoustic environment would implicitly be the sum of distances to opposite walls with respect to an ordinal audio processing device).
Regarding claim 5, Zhou, as modified in view of Dokmanic teaches the method of claim 1. Dokmanic further discloses wherein the device location data includes distances between each of the plurality of audio processing devices (Fig. 3,[0073]-[0074], array of four microphones is set up with an arbitrarily placed source. Geometry is selected to allow receivers to pick up first-order echoes. R1 to R4 denotes the receivers along with their positions).
Regarding claim 6, Zhou, as modified in view of Dokmanic teaches the method of claim 1. Zhou further discloses the plurality of candidate wall distance estimates includes candidate wall distance estimates for a first audio processing device of the plurality of audio processing devices, wherein the candidate wall distance estimates for the first audio processing device have highest confidence scores from among candidate wall distance estimates for the first audio processing device ([pg. 5], echo candidates are generated for both microphones and a probabilistic evidence accumulation method is conducted for each candidate. Candidates with the greatest probabilities are then used to determine path length to a given wall. Depending on the path, top microphone or bottom microphone may be better for localizing a particular wall.).
Regarding claim 7, Zhou, as modified in view of Dokmanic teaches the method of claim 1. Dokmanic teaches further discloses the location of each wall in the plurality of walls relative to the ordinal audio processing device includes at least one of towards a front of the ordinal audio processing device, towards to a back the ordinal audio processing device, towards a left of the ordinal audio processing device, or towards a right of the ordinal audio processing device(Implicit, Fig. 3, [0073]-[0082], a 4 microphone array is situated in a 2D room and a loudspeaker is set up at an arbitrary position. If the loudspeaker fires a pulse, each microphone picks up echoes for all of the walls. In order to know which peaks in an impulse response corresponds to each wall, point sets in Euclidean spaces are used and echoes associated with particular walls are ranked. In two dimensions, the ranks go up to 4.)(Fig. 3 illustrates a wall in front of, behind, to the left of, and to the right of, a given microphone selected as the ordinal microphone).
Regarding claim 8, Zhou, as modified in view of Dokmanic teaches the method of claim 1. Dokmanic further teaches generating the room layout matrix comprises: associating, based on a highest confidence score in the plurality of confidence scores for a first audio processing device from the plurality of audio processing devices, a candidate wall distance associated with the highest confidence score with the wall towards a front of the first audio processing application; associating, based on a second highest confidence score in the plurality of confidence scores for the first audio processing device from the plurality of audio processing devices, a candidate wall distance associated with the second highest confidence score with the wall towards a left of the first audio processing application; associating, based on a third highest confidence score in the plurality of confidence scores for the first audio processing device from the plurality of audio processing devices, a candidate wall distance associated with the third highest confidence score with the wall towards a right of the first audio processing application; and associating, based on a lowest confidence score in the plurality of confidence scores for the first audio processing device from the plurality of audio processing devices, a candidate wall distance associated with the lowest confidence score with the wall towards a back of the first audio processing application (Implicit, Fig. 3, [0073]-[0082], a 4 microphone array is situated in a 2D room and a loudspeaker is set up at an arbitrary position. If the loudspeaker fires a pulse, each microphone picks up echoes for all of the walls. In order to know which peaks in an impulse response corresponds to each wall, point sets in Euclidean spaces are used and echoes associated with particular walls are ranked. In two dimensions, the ranks go up to 4.)(it is the examiner’s interpretation that depending on the positioning of the speaker and the direction of the emitted pulse, the highest rank would be assigned to the wall in front of the first speaker, the second rank to the wall to the left, the third rank to the right, and the fourth rank to the rear).
Regarding claim 9, Zhou, as modified in view of Dokmanic teaches the method of claim 1. Zhou further teaches the plurality of candidate wall distances estimates includes at least one of a ceiling distance estimate or a floor distance estimate ([pg. 7], by adjusting the orientation of the phone, the user can generate floor or ceiling distance estimates).
Regarding claim 12, Zhou, as modified in view of Dokmanic teaches the method of claim 1, wherein determining the set of wall distance estimates further comprises: determining that the highest confidence score in a first column of the room layout matrix is associated with the ordinal audio processing device([pg. 4], for each emitted chirp, multiple peaks corresponding to different echoes are detected. Using a threshold, only the top-K strongest peaks are selected. Top 6 peaks are chosen for the top microphone, and top 10 peaks are chosen for the bottom microphone)([pg. 5], echo candidates are generated for both microphones and a probabilistic evidence accumulation method is conducted for each candidate. Candidates with the greatest probabilities are then used to determine path length to walls.);
Dokmanic further teaches determining the set of wall distance estimates from the ordinal audio processing device includes a candidate wall distance estimate of the plurality of candidate wall distance estimates associated with the highest confidence score in the first column of the room layout matrix(Implicit, Fig. 3, [0073]-[0082], a 4 microphone array is situated in a 2D room and a loudspeaker is set up at an arbitrary position. If the loudspeaker fires a pulse, each microphone picks up echoes for all of the walls. In order to know which peaks in an impulse response corresponds to each wall, point sets in Euclidean spaces are used and echoes associated with particular walls are ranked. In two dimensions, the ranks go up to 4.).
Regarding claim 14, the claim is a CRM claim corresponding to claim 1 and is therefore rejected for the same reasons.
Regarding claim 15, the claim is a CRM claim corresponding to claim 6 and is therefore rejected for the same reasons.
Regarding claim 16, the claim is a CRM claim corresponding to claim 8 and is therefore rejected for the same reasons.
Regarding claim 19, the claim is a CRM claim corresponding to claim 12 and is therefore rejected for the same reasons.
Regarding claim 20, the claim is a system claim corresponding to claim 1 and is therefore rejected for the same reasons.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhou in view of Dokmanic and Ribeiro et al. ("Geometrically constrained room modeling with compact microphone arrays." IEEE Transactions on Audio, Speech, and Language Processing 20.5 (2011): 1449-1460., “Ribeiro”).
Regarding claim 13, Zhou, as modified in view of Dokmanic teaches the method of claim 1. Zhou, as modified in view of Dokmanic may not explicitly teach determining, based on the one or more room layout estimates, an acoustic model of the acoustic environment; processing one or more audio signals using the acoustic model; and emitting the one or more processed audio signals using one or more speakers.
Ribeiro teaches determining, based on the one or more room layout estimates, an acoustic model of the acoustic environment; processing one or more audio signals using the acoustic model; and emitting the one or more processed audio signals using one or more speakers ([pg. 4], method of room modelling starts with obtaining synthetically/experimentally obtained wall impulse responses in order to generate room impulse responses. Wall validation is then performed by applying a regularization parameter that fits the measured impulse response with the dominant wall impulse responses.)(Implicit, [pg. 7], to generate a set of wall impulse responses suitable for interpolation, templates should be used based on the types of microphones that will be used as they are device dependent)(it is the examiner’s interpretation that the signal emitted from the speaker would be processed and emitted based on the type of microphones used in wall impulse response estimation in order to reduce the impulse response mismatch).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art of acoustic floorplan reconstruction, before the effective filing date of the claimed invention, to modify the method of Zhou, as modified in view of Dokmanic to include the acoustic modelling and processed signal emission of Ribeiro with a reasonable expectation of success, with the motivation of reducing the mismatch of the measured impulse responses received at the microphones [pg. 7].
Allowable Subject Matter
Claims 10-11 and 17-18 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims as well as overcoming any relevant 35 USC 112(b) rejections.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claim 10, Zhou, as modified in view of Dokmanic teaches the method of claim 1. Zhou further teaches determining the set of wall distance estimates further comprises: determining that the highest confidence score in a first column of the room layout matrix is associated with a first audio processing device that is different from the ordinal audio processing device; and adding the distance to the wall distance estimate associated with the highest confidence score in the first column([pg. 4], for each emitted chirp, multiple peaks corresponding to different echoes are detected. Using a threshold, only the top-K strongest peaks are selected. Top 6 peaks are chosen for the top microphone, and top 10 peaks are chosen for the bottom microphone)([pg. 5], echo candidates are generated for both microphones and a probabilistic evidence accumulation method is conducted for each candidate. Candidates with the greatest probabilities are then used to determine path length to walls, However Zhou fails to teach the distance between the first audio processing device and the ordinal processing device being added to the wall distance estimate. No other identified prior art teaches this limitation in part with sufficient motivation to combine).
Dokmanic teaches determining a distance between the first audio processing device and the ordinal audio processing device in a direction associated with an orientation of a first wall corresponding to the first column (Fig. 3,[0073]-[0074], array of four microphones is set up with an arbitrarily placed source. Geometry is selected to allow receivers to pick up first-order echoes. R1 to R4 denotes the receivers along with their positions)(it is the examiner’s interpretation that the determination of each microphones positioning with respect to each other amounts to determining a distance between them being measured)( However Dokmanic fails to teach the distance between the first audio processing device and the ordinal processing device being added to the wall distance estimate. No other identified prior art teaches this limitation in part with sufficient motivation to combine).
Regarding claim 11, Zhou, as modified in view of Dokmanic teaches the method of claim 1. Zhou further teaches determining the set of wall distance estimates further comprises: determining that the highest confidence score in a first column of the room layout matrix is associated with a first audio processing device that is different from the ordinal audio processing device; and subtracting the distance from the wall distance estimate associated with the highest confidence score in the first column([pg. 4], for each emitted chirp, multiple peaks corresponding to different echoes are detected. Using a threshold, only the top-K strongest peaks are selected. Top 6 peaks are chosen for the top microphone, and top 10 peaks are chosen for the bottom microphone)([pg. 5], echo candidates are generated for both microphones and a probabilistic evidence accumulation method is conducted for each candidate. Candidates with the greatest probabilities are then used to determine path length to walls, However Zhou fails to teach the distance between the first audio processing device and the ordinal processing device being subtracted from the wall distance estimate. No other identified prior art teaches this limitation in part with sufficient motivation to combine).
Dokmanic further teaches determining a distance between the first audio processing device and the ordinal audio processing device in a direction associated with an orientation of a first wall corresponding to the first column(Fig. 3,[0073]-[0074], array of four microphones is set up with an arbitrarily placed source. Geometry is selected to allow receivers to pick up first-order echoes. R1 to R4 denotes the receivers along with their positions)(it is the examiner’s interpretation that the determination of each microphones positioning with respect to each other amounts to determining a distance between them being measured)( However Dokmanic fails to teach the distance between the first audio processing device and the ordinal processing device being added to the wall distance estimate. No other identified prior art teaches this limitation in part with sufficient motivation to combine);
Regarding claim 17, the claim is a CRM claim corresponding to claim 10 and is therefore indicated as containing allowable subject matter for the same reasons.
Regarding claim 18, the claim is a CRM claim corresponding to claim 11 and is therefore indicated as containing allowable subject matter for the same reasons.
Conclusion
Prior art made of record though not relied upon in the present basis of rejection are noted in the attached PTO 892 and include:
Pradhan et al. ("Smartphone-based acoustic indoor space mapping." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2.2 (2018): 1-26., “Pradhan”) which discloses a system and method for acoustic indoor space mapping
Lovedee-Turner et al. ("Three-dimensional reflector localisation and room geometry estimation using a spherical microphone array." The Journal of the Acoustical Society of America 146.5 (2019): 3339-3352., “Turner”) which teaches a method and system for acoustically estimating room geometry
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/CHRISTOPHER RICHARD WALKER/Examiner, Art Unit 3645
/YUQING XIAO/Supervisory Patent Examiner, Art Unit 3645