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.
Claims 2-4 and 13-15 are 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.
Regarding claims 2 and 13, the claims recites the limitation "the set of wall distance elements". There is insufficient antecedent basis for this limitation in the claim. Claims 1 and 12, from which claims 2 and 13 depend (respectively), recite “a set of wall distance estimates”, however makes no recitation of “a set of wall distance elements”. It is unclear what values comprise the set of wall distance elements, or whether it is intended to state “the set of wall distance estimates”, therefore the claim is unclear and thus indefinite. It is the examiner’s interpretation that “the set of wall distance elements” is intended to state “the set of wall distance estimates”.
Regarding claims 3-4 and 14-15, the claims are rejected due to their respective dependence upon a rejected base claim.
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, 9-10, 12, 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 comprising: emitting a reference audio signal using one or more speakers of an audio processing device located in an acoustic environment; receiving, by each microphone in a microphone pair of the audio processing device, a response of the acoustic environment to the reference audio signal;; determining, based on the impulse response, a plurality of candidate wall distance estimates 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; and determining based on the plurality of candidate wall distance estimates, the plurality of confidence scores, and candidate wall distance estimates and confidence scores received from one or more audio processing devices, a set of wall distance estimates, each wall distance estimate in the set of wall distance estimates being associated with a different wall in a plurality of walls in the acoustic environment([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 determining an impulse response of the acoustic environment based on the reference audio signal and the received response of the acoustic environment; and determining based on the plurality of candidate wall distance estimates, the plurality of confidence scores, and candidate wall distance estimates and confidence scores received from one or more other audio processing devices.
Dokmanic teaches determining an impulse response of the acoustic environment based on the reference audio signal and the received response of the acoustic environment. ([0035]-[0036] echo labelling is performed on received impulse responses in a room that are received by receivers and correspond to reflective surfaces such as walls. Euclidean distance matrices are used to augmented with a plurality of TOA values) (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)) and determining based on the plurality of candidate wall distance estimates, the plurality of confidence scores, and candidate wall distance estimates and confidence scores received from one or more other audio processing devices([0073]-[0074] Fig. 3 illustrates 4 microphones that enable the pick-up of first order echoes)(it is the examiner’s interpretation that the 4 separate microphones enable the generation of wall distance estimates from an “other audio processing device”).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art of acoustic room mapping, before the effective filing date of the claimed invention, to modify the method of Zhou, to include the impulse response based confidence score wall distance estimates with a reasonable expectation of success, with the motivation of reconstructing the geometry of the room using the locations of microphones and speaker to determine the locations in which a first order reflection reflects off of a wall [0073]-[0082].
Regarding claim 9, Zhou, as modified in view of Dokmanic teaches the method of claim 1. Zhou further teaches the audio processing device and the other audio processing devices are located at a same height from a floor of the acoustic environment ([pg. 4], user traces and acoustic distance measurements are combined for fast, light weight, and accurate corridor construction by the user holding their phone horizontally)(Fig. 4 illustrates the user phone having a top and bottom microphone)(it is the examiner’s interpretation that the user phone being held horizontally results in the two microphones being at the same height from a floor of the acoustic environment).
Regarding claim 10, Zhou, as modified in view of Dokmanic teaches the method of claim 1. Dokmanic further teaches the candidate wall distance estimates and confidence scores received from a second audio processing device of the one or more other audio processing devices are based on one or more other impulse responses determined by the second audio processing device ([0035]-[0036] echo labelling is performed on received impulse responses in a room that are received by receivers and correspond to reflective surfaces such as walls. Euclidean distance matrices are used to augmented with a plurality of TOA values) (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)).
Regarding claim 12, the claim is a CRM claim corresponding to claim 1 and is therefore rejected for the same reasons.
Regarding claim 19, the claim is a CRM claim corresponding to claim 10 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) 2-3, 5-6, 13-14, and 16-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhou in view of Dokmanic and Mabande et al. ("Room geometry inference based on spherical microphone array eigenbeam processing." The Journal of the Acoustical Society of America 134.4 (2013): 2773-2789., “Mabande”).
Regarding claim 2, Zhou, as modified in view of Dokmanic teaches the method of claim 1. Zhou, as modified in view of Dokmanic may not explicitly disclose determining the set of wall distance elements comprises clustering the plurality of candidate wall distance estimates associated with a first microphone in the microphone pair.
Mabande teaches determining the set of wall distance elements comprises clustering the plurality of candidate wall distance estimates associated with a first microphone in the microphone pair ([pg. 8-9], plane parameters are clustered based on whether or not they approximate the same boundary. In order to group the estimated planes into sets, all planes which estimate the same room boundary are clustered. Each column in the resulting matrix approximates the same room boundary).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art of acoustic room mapping, before the effective filing date of the claimed invention, to modify the method of Zhou, as modified in view of Dokmanic to include the clustering of Mabande with a reasonable expectation of success, with the motivation of creating a matrix in which the columns all define a set of planes that are grouped together to define the same room boundary [pg. 9].
Regarding claim 3, Zhou, as modified in view of Dokmanic and Mabande teaches the method of claim 2. Zhou further teaches clustering the plurality of candidate wall distance estimates associated with the first microphone comprises: determining that a first candidate wall distance estimate of the plurality of candidate wall distance estimates associated with the first microphone is within a threshold distance from a second candidate wall distance estimate of the plurality of candidate wall distance estimates associated with the first microphone; and removing the first candidate wall distance estimate from the plurality of candidate wall distance estimates ([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 selecting only the candidates with the greatest probabilities is equivalent to removing some of the candidate wall distance estimates, and that there would implicitly be instances in which a first wall distance estimate does not have one of the greatest probabilities and is therefore removed).
Regarding claim 5, 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 the set of wall distance estimates comprises clustering the plurality of candidate walls distance estimates associated with different microphones in the microphone pair together.
Mabande determining the set of wall distance estimates comprises clustering the plurality of candidate walls distance estimates associated with different microphones in the microphone pair together([pg. 8-9], plane parameters are clustered based on whether or not they approximate the same boundary. In order to group the estimated planes into sets, all planes which estimate the same room boundary are clustered. Each column in the resulting matrix approximates the same room boundary)(it is the examiner’s interpretation that so long as the measurements correspond to the same wall, they will be associated in the same cluster regardless of whether they correspond to the same or different microphones).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art of acoustic room mapping, before the effective filing date of the claimed invention, to modify the method of Zhou, as modified in view of Dokmanic to include the clustering of Mabande with a reasonable expectation of success, with the motivation of creating a matrix in which the columns all define a set of planes that are grouped together to define the same room boundary [pg. 9].
Regarding claim 6, Zhou, as modified in view of Dokmanic and Mabande teaches the method of claim 5. Zhou further teaches clustering the plurality of candidate wall distance estimates associated with the different microphones comprises: determining that a first candidate wall distance estimate of the plurality of candidate wall distance estimates associated with a first microphone in the microphone pair is within a threshold distance from a second candidate wall distance estimate of the plurality of candidate wall distance estimates associated with a second microphone in the microphone pair; and determining the set of wall distance estimates includes at least one of the first candidate wall distance estimate of the plurality of candidate wall distance estimates associated with the first microphone or the second candidate wall distance estimate of the plurality of candidate wall distance estimates associated with the second 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. Calculations are conducted to infer which path the echo belongs to and which microphone each path corresponds to)(it is the examiner’s interpretation that the candidate list only being applied to a particular wall is equivalent to the first and second candidate wall distance being within a threshold distance. Additionally, it is the examiner’s interpretation that the determination of the paths associated with each respective echo is equivalent to determining whether the plurality of candidate wall distance estimates corresponds to a first microphone or second microphone).
Regarding claim 13, the claim is a CRM claim corresponding to claim 2 and is therefore rejected for the same reasons.
Regarding claim 14, the claim is a CRM claim corresponding to claim 3 and is therefore rejected for the same reasons.
Regarding claim 16, the claim is a CRM claim corresponding to claim 5 and is therefore rejected for the same reasons.
Regarding claim 17, the claim is a CRM claim corresponding to claim 6 and is therefore rejected for the same reasons.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhou in view of Dokmanic and Florencio et al. (US 20110317522 A1, “Florencio”).
Regarding claim 8, Zhou, as modified in view of Dokmanic teaches the method of claim 1. Zhou, as modified in view of Dokmanic may not explicitly disclose the reference audio signal comprises a sine sweep.
Florencio teaches the reference audio signal comprises a sine sweep ([0022], in order to determine the room’s acoustic characteristics, the device actively probes the room by emitting an known signal such as a linear sweep).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art of acoustic room mapping, before the effective filing date of the claimed invention, to modify the method of Zhou, as modified in view of Dokmanic to include the sine sweep of Florencio with a reasonable expectation of success, with the motivation of determining a room’s acoustic characteristics [0022].
Claim(s) 11 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 11, 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 set of wall distance 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 the one or more speakers.
Ribeiro teaches determining, based on the set of wall distance 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 the 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 room mapping, before the effective filing date of the claimed invention, to modify the method of Zhou, as modified in view of Dokmanic to include the modeling 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 4, 7, 15, and 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 U.S.C. 1112(b) rejections.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claim 4, Zhou, as modified in view of Dokmanic and Mabande teaches the method of claim 3. Zhou further teaches removing the first candidate wall distance estimate from the plurality of candidate wall distance estimates comprises: determining that a confidence score associated with the second candidate wall distance estimate is higher than a confidence score associated with the first candidate wall distance estimate; and determining, based on averaging the confidence score associated with the first candidate wall distance estimate and the confidence score associated with the second candidate wall distance estimate, a new confidence score associated with the second candidate wall distance estimate([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 required limitation of averaging candidate wall distance measurements from a first and second microphone in order to generate a new confidence score. No other identified prior art teaches this limitation wholly or in part with sufficient motivation to combine).
Regarding claim 7, Zhou discloses the method of claim 1. Zhou further discloses determining a most common wall distance estimate in the plurality of candidate wall distance estimates and the candidate wall distance estimates received from the one or more other audio processing devices; and identifying the most common wall distance estimate as a ceiling distance estimate([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.)([pg. 7], the user can hold the phone vertically and measure the distance to the ceiling. However Zhou fails to teach the required limitation of identifying a wall distance measurement value that occurs most frequently as belonging to the ceiling. No other identified prior art teaches this limitation wholly or in part with sufficient motivation to combine).
Regarding claim 15, the claim is a CRM claim corresponding to claim 4 and is therefore rejected for the same reasons.
Regarding claim 18, the claim is a CRM claim corresponding to claim 7 and is therefore rejected 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:
Chen et al. (US 11125553 B2, “Chen”) which discloses methods and systems for room shape reconstruction and self-localization using first-order acoustic echoes
Zhou et al. (US 20210207974 A1, “Zhou 2”) which discloses a system and method for determination of objects within a bounded perimeter of a 3D space based on acoustic echo signatures
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER RICHARD WALKER whose telephone number is (571)272-6136. The examiner can normally be reached Monday - Friday 7:30 am - 5:00 pm.
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/CHRISTOPHER RICHARD WALKER/Examiner, Art Unit 3645
/YUQING XIAO/Supervisory Patent Examiner, Art Unit 3645