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 .
DETAILED ACTION
Claim Rejections - 35 USC § 102
1. 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
2. Claims 1 and 13 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by submitted prior art Matsunaga (2018/0301129) and/or Iwase (2009/0031886).
As to claim 1, Matsunaga teaches a system comprising: a plurality of resonator circuits (Fig. 3, resonance circuits 14a-c, 15a-c and 16a-c) wherein different resonator circuits are tuned to generate different output frequencies ([0038] – the signal output from the resonator corresponding to a respective key vibrates at least at the corresponding pitch fundamental frequency); an excitation signal that when applied to the plurality of resonator circuits causes one or more resonators circuits in the plurality of resonator circuits to output a signal at an associated frequency ([0038] – the signal output from the resonator corresponding to a respective key vibrates at least at the corresponding pitch fundamental frequency; Fig. 3 – with the output from the corresponding groups 1, 2, or 3); and acoustic effects module (delay circuits can be used to model the acoustic effects of resonator circuits, and in some cases they are directly equivalent to acoustic delay lines or waveguide models) for applying one or more acoustic effects to selected frequencies from a frequency spectrum generated by the plurality of resonator circuits (delay circuits 17R-L, 18R-L, 19R-L for receiving a frequency response derived from the excitation of the plurality of resonator circuits (Fig. 3 – with the output from the corresponding groups 1, 2, or 3) and applying one or more acoustic effects ([0021-0022] – with the stereo delay effect) to selected frequencies from the frequency response ([0039-0040] – with the delay applied by circuits 17R, 17L to resonance circuits of key group 1, corresponding to selected frequencies of keys belonging to group 1 generated by the plurality of resonator circuits (Fig. 3, resonators circuits).
OR
As to claim 1, Iwase teaches a system comprising: a plurality of resonator circuits ([0014] - resonators and a first adder, the resonators generating resonance sound data of given resonant frequencies based on sound signal data corresponding to a pitch of a key which is struck, each of the resonators including a delay circuit configured to delay an input based on delay time data indicating a delay time, a second adder configured to add an output from the delay circuit to input sound signal data, and a first low-pass filter configured to receive an output from the second adder and to perform low-pass filtering by a cutoff frequency depending on a filter control signal on the output from the second adder, and an output from the first low-pass filter inputting to the delay circuit, and the first adder adding outputs from the resonators) wherein different resonator circuits are tuned to generate different output frequencies ([0041-0042] - The delay time data D from the delay controller 44 enables adjustment of a resonant frequency of resonance data output from the resonators, and the filter control data F from the filter controller 43 enables adjustment (suppression) of a resonance level of the resonators and [0055-0056] – each group is composed of resonators having dedicated and adjustable resonance frequencies); an excitation signal that when applied to the plurality of resonators circuits caused one or more resonator circuits in the plurality of resonator circuits to output a signal at an associated frequency ([0041-0042] - The delay time data D from the delay controller 44 enables adjustment of a resonant frequency of resonance data output from the resonators, and the filter control data F from the filter controller 43 enables adjustment (suppression) of a resonance level of the resonators; sound generated are sent to resonator groups (Fig.2, 33 & 34 and [0041, 0045]) and [0055-0056] – each group is composed of resonators having dedicated and adjustable resonance frequencies); and an acoustic effects module (delay circuits can be used to model the acoustic effects of resonator circuits, and in some cases they are directly equivalent to acoustic delay lines or waveguide models) for applying one or more acoustic effects to selected frequencies from a frequency spectrum generated by the plurality of resonator circuits (the delay time data D from the delay controller 44 enables adjustment of a resonant frequency of resonance data output from the resonators, and the filter control data F from the filter controller 43 enables adjustment (suppression) of a resonance level of the resonators ([0041-0042]); sound generated are sent to resonator groups (Fig.2, 33 & 34 and [0041, 0045]) and [0055-0056] – each group is composed of resonators having dedicated and adjustable resonance frequencies and the output resonance signal (i.e. frequency response derived from the excitation of the plurality of resonator circuits) of each group is treated by a corresponding filter (Fig. 2, filters 35 & 36) and [0046-0047, 0078-0080] - each providing the left and right adjusted resonance signals (Fig. 2); the filters could a combination of low-pass and high-pass filter in series where LPF and HPF apply frequency selective damping and phase shift to the frequency response).
As to claim 13, Matsunaga teaches a method for producing and audio output from a plurality of resonator circuits comprising: receiving at the plurality of resonator circuits (Fig. 3, resonance circuits 14a-c, 15a-c and 16a-c) wherein different resonator circuits are tuned to generate different output frequencies ([0038] – the signal output from the resonator corresponding to a respective key vibrates at least at the corresponding pitch fundamental frequency); an excitation signal that when applied to the plurality of resonator circuits causes one or more resonators circuits in the plurality of resonator circuits to output a signal at an associated frequency ([0038] – the signal output from the resonator corresponding to a respective key vibrates at least at the corresponding pitch fundamental frequency; Fig. 3 – with the output from the corresponding groups 1, 2, or 3); in an acoustic effects module (delay circuits can be used to model the acoustic effects of resonator circuits, and in some cases they are directly equivalent to acoustic delay lines or waveguide models) for applying one or more acoustic effects to selected number of the plurality of resonator circuits and producing from the plurality of resonator circuits and acoustic signal based on the excitation signal and the applied acoustic effects (delay circuits 17R-L, 18R-L, 19R-L for receiving a frequency response derived from the excitation of the plurality of resonator circuits (Fig. 3 – with the output from the corresponding groups 1, 2, or 3) and applying one or more acoustic effects ([0021-0022] – with the stereo delay effect) to selected frequencies from the frequency response ([0039-0040] – with the delay applied by circuits 17R, 17L to resonance circuits of key group 1, corresponding to selected frequencies of keys belonging to group 1 generated by the plurality of resonator circuits (Fig. 3, resonators circuits).
OR
As to claim 13, Iwase teaches a method for producing and audio output from a plurality of resonator circuits comprising: receiving at the plurality of resonator circuits ([0014] - resonators and a first adder, the resonators generating resonance sound data of given resonant frequencies based on sound signal data corresponding to a pitch of a key which is struck, each of the resonators including a delay circuit configured to delay an input based on delay time data indicating a delay time, a second adder configured to add an output from the delay circuit to input sound signal data, and a first low-pass filter configured to receive an output from the second adder and to perform low-pass filtering by a cutoff frequency depending on a filter control signal on the output from the second adder, and an output from the first low-pass filter inputting to the delay circuit, and the first adder adding outputs from the resonators), an excitation signal to produce a frequency from at least one of the plurality of resonators circuits ([0041-0042] - the delay time data D from the delay controller 44 enables adjustment of a resonant frequency of resonance data output from the resonators, and the filter control data F from the filter controller 43 enables adjustment (suppression) of a resonance level of the resonators; sound generated are sent to resonator groups (Fig.2, 33 & 34 and [0041, 0045]) and [0055-0056] – each group is composed of resonators having dedicated and adjustable resonance frequencies); an acoustic effects module (delay circuits can be used to model the acoustic effects of resonator circuits, and in some cases they are directly equivalent to acoustic delay lines or waveguide models) for applying one or more acoustic effects to selected number of the plurality of resonator circuits and producing an acoustic signal based the applied acoustic effect (the delay time data D from the delay controller 44 enables adjustment of a resonant frequency of resonance data output from the resonators, and the filter control data F from the filter controller 43 enables adjustment (suppression) of a resonance level of the resonators ([0041-0042]); sound generated are sent to resonator groups (Fig.2, 33 & 34 and [0041, 0045]) and [0055-0056] – each group is composed of resonators having dedicated and adjustable resonance frequencies and the output resonance signal (i.e. frequency response derived from the excitation of the plurality of resonator circuits) of each group is treated by a corresponding filter (Fig. 2, filters 35 & 36) and [0046-0047, 0078-0080]) each providing the left and right adjusted resonance signals (Fig. 2); the filters could a combination of low-pass and high-pass filter in series where LPF and HPF implicitly apply frequency selective damping and phase shift to the frequency response); and producing, from the plurality of resonator circuits, an acoustic signal based on the excitation signal ([0041-0042] - The delay time data D from the delay controller 44 enables adjustment of a resonant frequency of resonance data output from the resonators, and the filter control data F from the filter controller 43 enables adjustment (suppression) of a resonance level of the resonators; sound generated are sent to resonator groups (Fig.2, 33 & 34 and [0041, 0045]) and [0055-0056] – each group is composed of resonators having dedicated and adjustable resonance frequencies).
Claim Rejections - 35 USC § 103
3. 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.
4. Claims 2-4 are rejected under 35 U.S.C. 103 as being unpatentable over Matsunaga and/or Iwase in view of Alfonso (US Patent 12,210,095).
As to claim 2, Matsunaga and/or Iwase does not explicitly discuss the device of claim 1, wherein the one or more acoustic effects is selected from one or more of phase advance, an amplitude level, and a decay interval.
Alfonso teaches one or more acoustic effects is selected from one or more of phase advance, an amplitude level, and a decay interval (col. 13, lines 11-22 - the acoustic characteristics are values that are added to the point definition, and may specify how different sound frequencies are affected when colliding with or coming into contact with the point cloud points that are defined with those acoustic characteristics. The sound effects defined by the acoustic characteristics may include specifying an amount by which certain frequencies are absorbed or reflected, adjustments to apply to different frequencies, adding echo, reverberation, distortion, changing tone, timbre adjustments, amplitude adjustments, loudness adjustments, and/or specifying other changes to the sound or sound properties).
It would have been obvious before the effective filing date of the claimed invention to incorporate the teachings of Alfonso into Matsunaga and/or Iwase for the purpose of adding echo, reverberation, distortion, changing tone, timbre adjustments, amplitude adjustments, loudness adjustments, and/or specifying other changes to the sound or sound properties.
As to claim 3, Matsunaga and/or Iwase and Alfonso do not explicitly discuss the device of claim 1, wherein the one or more acoustic effects comprising a set of parameters comprising an input to a first resonator circuit of the plurality of circuits. However, Alfonso teaches the sound effects defined by the acoustic characteristics may include specifying an amount by which certain frequencies are absorbed or reflected, adjustments to apply to different frequencies, adding echo, reverberation, distortion, changing tone, timbre adjustments, amplitude adjustments, loudness adjustments, and/or specifying other changes to the sound or sound properties are values that are added to the point definition, and may specify how different sound frequencies are affected when colliding with or coming into contact with the point cloud points that are defined with those acoustic characteristics (col. 13, lines 11-22); and input component 940 may include a mechanism that permits an operator to input information to device 900, such as a keyboard, a keypad, a button, a switch, etc. (col. 16, lines 24-26). It would have been obvious to modify Alfonso’s system that permits to input information to a resonator circuit to apply acoustic effects parameters to selected frequency generated by the resonator circuit.
As to claim 4, Alfonso teaches the device of claim 1, further comprising: an input port for receiving a user input device (col. 16, lines 24-26 - input component 940 may include a mechanism that permits an operator to input information to device 900, such as a keyboard, a keypad, a button, a switch, etc.).
5. Claims 5-7 are rejected under 35 U.S.C. 103 as being unpatentable over Matsunaga and/or Iwase and Alfonso in view of Elson (US Patent 10,410,614).
As to claim 5, Matsunaga and/or Iwase and Alfonso do not explicitly discuss the device of claim 4, wherein the user input is a musical keyboard.
Elson teaches receiving commands via a keyboard note key (e.g., when an instrument has a keyboard) (col. 19, lines 45-47); receiving a command from the remote receiver (which in turn received the command from the local receiver), the remote instrument, which may be a computing device acting as a synthesizer or coupled to a digital keyboard, piano, guitar or other instrument (col. 8, lines 24-28).
It would have been obvious before the effective filing date of the claimed invention to incorporate the teachings of Elson into the teachings of Matsunaga and/or Iwase and Alfonso for the purpose of receiving commands via a keyboard note key.
As to claim 6, Elson teaches the device of claim 4, wherein the user input is a musical instrument digital interface (MIDI) controller (col. 5, lines 24-28 - the musical instrument may generate instrument digital commands (e.g., MIDI commands). The digital recording may be in the form of stored instrument digital commands (e.g., MIDI commands) or a digital recording of analog music; col. 6, lines 8-22).
As to claim 7, Elson teaches receiving commands via a keyboard note key (e.g., when an instrument has a keyboard), the commands may also be received via other input mechanisms, such as, by way of non-limiting example, instrument strings (e.g., when an instrument has strings), via a resonator blown into by a user or air pump (such as an instrument that has a wind component, such as a trumpet, clarinet, oboe, flute, etc.), or via a percussive element (e.g., which an instrument has a percussive component) (col. 19, lines 45-53); and when the user provides an input or activates a control, a corresponding computing system may perform a corresponding operation (e.g., store the user input, process the user input, provide a response to the user input, etc.) (col. 45, line 67 through col. 46, line 3). Alfonso teaches the acoustic characteristics are values that are added to the point definition, and may specify how different sound frequencies are affected when colliding with or coming into contact with the point cloud points that are defined with those acoustic characteristics. The sound effects defined by the acoustic characteristics may include specifying an amount by which certain frequencies are absorbed or reflected, adjustments to apply to different frequencies, adding echo, reverberation, distortion, changing tone, timbre adjustments, amplitude adjustments, loudness adjustments, and/or specifying other changes to the sound or sound properties (col. 13, lines 11-22). It would have been obvious to incorporate the teachings of Alfonso into the teachings of Elson to apply one or more sound effects to selected frequency of the user input in order to provide user opportunity to select different frequencies with different sound effects as desired.
6. Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Matsunaga and/or Iwase in view of Gou et al. (2024/0347054).
As to claim 8, Matsunaga and/or Iwase does not explicitly discuss the device of claim 1, further comprising an artificial intelligence (AI) network in communication with the acoustic effects module.
Gou teaches a series of training texts 510 and their standard pronunciation audio 512 are input into the aforementioned data preprocessing system 110, to be converted into training phonetic symbols 514 and training audio data 516 by the phonetic symbol generation system 112 (including the artificial intelligence model 124) ... The language model construction system 506 trains the language model 502 based on the training phonetic symbols 514. The acoustic model construction system 508 trains the acoustic model 504 based on the training phonetic symbols 514 as well as the training audio data 516. Under this design, the language model 502 may be well-trained by the language model construction system 506 based on the high-accuracy training phonetic symbols 514. Similarly, the acoustic model 504 the acoustic model may be well-trained to have better acoustic simulation effects by the construction system 508 based on the high-accuracy training phonetic symbols ([0064]).
It would have been obvious before the effective filing date of the claimed invention to incorporate the teachings of Gou into the teachings of Matsunaga and/or Iwase for the purpose of having a well-trained acoustic model for better acoustic simulation effects.
7. Claims 9-12 are rejected under 35 U.S.C. 103 as being unpatentable over Matsunaga and/or Iwase and Gou in view of Reams (2004/0013272).
As to claim 9, Matsunaga and/or Iwase and Gou do not explicitly discuss the device of claim 8, wherein the AI network stores a library of models, a model stored in the library providing inputs to the acoustic effects module for applying acoustic effects to frequencies selected by the AI network.
Reams teaches the spectral frequency bands can be selected corresponding to a number of artificial intelligence processing systems, such as neural network systems that are used to learn response characteristics for spectral frequency band gain settings … bandwidth reallocation can be selected based on predetermined selections from a library of characteristic sets, or other suitable processes can be performed ([0079]). Method 800 begins at 802 where spectral frequency bands are selected, the spectral frequency bands can be selected corresponding to a number of artificial intelligence processing systems, such as neural network systems that are used to learn response characteristics for spectral frequency band gain settings, these spectral frequency bands can be set to a user selected frequency range, to concentrate frequency bands in areas in which human hearing is most sensitive. Likewise, where any suitable number of frequency bands and corresponding artificial intelligence processing systems can be used, the spectral frequency bands can be selected based on the characteristics of the audio data, aesthetic qualities, or other suitable characteristics ([0079]), and adaptive gain settings are selected for each band, the adaptive gain settings can include one or more inputs, modifiers, conditionals, or other suitable characteristics that are used to control the generation of spectral gain characteristics. For example, adaptive gain settings can include threshold levels, response times, maximum gain settings, transfer functions settings, target levels, or other suitable adaptive gain settings. Bands can be used for each variable that are accessible absolutely or cumulatively, and can further include inputs based on other spectral frequency bands, such as gain levels or settings ([0080]).
It would have been obvious before the effective filing date of the claimed invention to incorporate the teachings of Reams into the teachings Iwase, Alfonso, and Gou for the purpose of performing bandwidth allocation selected based on predetermined selections from a library of characteristics set or other suitable processes can be performed.
As to claim 10, Reams teaches the audio device of claim 8, wherein the AI network is trained with audio samples having labels indicating if the audio samples contain a pleasing sound to a human ear ([0037] - Sample selection system 204 allows the user to mark and select portions of the sample audio data having suitable aesthetic characteristics. In one exemplary embodiment, spectral shaping system 106, image management system 108, and other suitable systems can include artificial intelligence systems, such as one or more neural networks or other suitable artificial intelligence systems, that can be trained using the sample audio data so as to provide improved processing control of the target audio data, sample selection system 204 tracks the number of data points required (which corresponds to the time length of the sample audio data), and allows the user to determine whether the audio sample has sufficient length to allow such artificial intelligence systems to be trained; and [0038] - if a 10-second sample is required in order to train certain artificial intelligence components, then sample selection system 204 can allow the user to listen to the sample audio data to determine whether the aesthetic characteristics are desirable while viewing a graphical display that indicates whether the sample has sufficient length, if there are only certain portions of the audio sample that have the aesthetic characteristics desired by the user, sample selection system 204 allows the user to mark those portions to determine which portions have an acceptable length, to assign a relative ranking to each portion, or to perform other suitable processes).
As to claim 11 Reams teaches the audio device of claim 8, wherein the AI network is trained to contain models that improve the aesthetic qualities of music and using the sample audio data so as to provide improved processing control of the target audio, emulate a particular musical instrument ([0037] - other suitable systems can include artificial intelligence systems, such as one or more neural networks or other suitable artificial intelligence systems, that can be trained using the sample audio data so as to provide improved processing control of the target audio data without operator intervention, sample selection system 204 tracks the number of data points required (which corresponds to the time length of the sample audio data), and allows the user to determine whether the audio sample has sufficient length to allow such artificial intelligence systems to be trained and [0091] - allowing audio image data characteristics to be generated from sample audio data, such as to reproduce the aesthetic qualities of the sample audio data. Method 900 also allows audio image data characteristics to be set or modified by user so as to provide aesthetic qualities not found in sample audio data, or for other suitable purposes. Method 900 can be used to minimize masking of perceptual queues so as to improve the aesthetic qualities of music by decreasing listener fatigue, masking or other undesirable characteristics of the music; [0004] - Audio data processing thus focuses on several concepts: spectral shaping and audio image. Spectral shaping refers to the settings of equalization bands, whereas audio image refers to the three-dimensional characteristic of stereophonic audio data as heard by a listener. For example, a listener in a room with two loudspeakers, one emitting stereophonic left channel signals and the other emitting stereophonic right channel signals, may seem to hear sound coming from the side of the room, the back of the room, or locations other than the two loudspeakers. The ability to present three-dimensional aesthetic qualities to music is referred to as the audio image of the audio data).
As to claim 12, Reams teaches the audio device of claim 8, wherein the AI network is trained to contain models that emulate a particular acoustic/audio space ([0037] - other suitable systems can include artificial intelligence systems, such as one or more neural networks or other suitable artificial intelligence systems, that can be trained using the sample audio data so as to provide improved processing control of the target audio data without operator intervention, sample selection system 204 tracks the number of data points required (which corresponds to the time length of the sample audio data), and allows the user to determine whether the audio sample has sufficient length to allow such artificial intelligence systems to be trained; and [0093] - The audio data can be received at a studio, an audio data processor, can be received by a listener, or other suitable audio data reception points can be established).
8. Claims 14-20 are rejected under 35 U.S.C. 103 as being unpatentable over Matsunaga and/or Iwase in view of Alfonso (US Patent 12,210,095), Reams (2004/0013272) and Andersen et al. (2013/0095759).
As to claim 14, Matsunaga and/or Iwase does not explicitly discuss the method of claim 13, further comprising: in a model of an artificial intelligence network, selecting one or more acoustic effects and the selected number of the plurality of resonator circuits; and providing the selected one or more audio effects and the selected number of resonator circuits to an acoustic effects module.
Alfonso teaches the acoustic characteristics are values that are added to the point definition, and may specify how different sound frequencies are affected when colliding with or coming into contact with the point cloud points that are defined with those acoustic characteristics. The sound effects defined by the acoustic characteristics may include specifying an amount by which certain frequencies are absorbed or reflected, adjustments to apply to different frequencies, adding echo, reverberation, distortion, changing tone, timbre adjustments, amplitude adjustments, loudness adjustments, and/or specifying other changes to the sound or sound properties (col. 13, lines 11-22). Iwase and Alfonso do not explicitly discuss in a model of an artificial intelligence (AI) network, selecting the selected number of the plurality of resonator circuits; providing the selected number of resonator circuits to an acoustic effects module.
Reams teaches the spectral frequency bands can be selected corresponding to a number of artificial intelligence processing systems, such as neural network systems that are used to learn response characteristics for spectral frequency band gain settings … bandwidth reallocation can be selected based on predetermined selections from a library of characteristic sets, or other suitable processes can be performed ([0079]). Method 800 begins at 802 where spectral frequency bands are selected, the spectral frequency bands can be selected corresponding to a number of artificial intelligence processing systems, such as neural network systems that are used to learn response characteristics for spectral frequency band gain settings, these spectral frequency bands can be set to a user selected frequency range, to concentrate frequency bands in areas in which human hearing is most sensitive. Likewise, where any suitable number of frequency bands and corresponding artificial intelligence processing systems can be used, the spectral frequency bands can be selected based on the characteristics of the audio data, aesthetic qualities, or other suitable characteristics ([0079]), and adaptive gain settings are selected for each band, the adaptive gain settings can include one or more inputs, modifiers, conditionals, or other suitable characteristics that are used to control the generation of spectral gain characteristics. For example, adaptive gain settings can include threshold levels, response times, maximum gain settings, transfer functions settings, target levels, or other suitable adaptive gain settings. Bands can be used for each variable that are accessible absolutely or cumulatively, and can further include inputs based on other spectral frequency bands, such as gain levels or settings ([0080]).
Andersen teaches the fundamental frequency corresponds to the resonance frequency of the selected resonator circuit of the reader and data carrier ([0029]).
It would have been obvious before the effective filing date of the claimed invention to incorporate the teachings of Alfonso, Reams and Andersen into the teachings Matsunaga and/or Iwase for the purpose of performing bandwidth allocation selected based on the selected resonator circuit and predetermined selections from a library of characteristics set or other suitable processes can be performed.
As to claim 15, Iwase teaches the method of claim 14 further comprising: a plurality of resonator circuits ([0014] - resonators and a first adder, the resonators generating resonance sound data of given resonant frequencies based on sound signal data corresponding to a pitch of a key which is struck, each of the resonators including a delay circuit configured to delay an input based on delay time data indicating a delay time, a second adder configured to add an output from the delay circuit to input sound signal data, and a first low-pass filter configured to receive an output from the second adder and to perform low-pass filtering by a cutoff frequency depending on a filter control signal on the output from the second adder, and an output from the first low-pass filter inputting to the delay circuit, and the first adder adding outputs from the resonators) wherein different resonator circuits are tuned to generate different output frequencies ([0041-0042] - The delay time data D from the delay controller 44 enables adjustment of a resonant frequency of resonance data output from the resonators, and the filter control data F from the filter controller 43 enables adjustment (suppression) of a resonance level of the resonators); an excitation signal that when applied to the plurality of resonators circuits caused one or more resonator circuits in the plurality of resonator circuits to output a signal at an associated frequency ([0041-0042] - The delay time data D from the delay controller 44 enables adjustment of a resonant frequency of resonance data output from the resonators, and the filter control data F from the filter controller 43 enables adjustment (suppression) of a resonance level of the resonators; sound generated are sent to resonator groups (Fig.2, 33 & 34 and [0041, 0045]) and [0055-0056] – each group is composed of resonators having dedicated and adjustable resonance frequencies); [0046-0047, 0078-0080] - each providing the left and right adjusted resonance signals (Fig. 2); the filters maybe a combination of low-pass and high-pass filter in series where LPF and HPF implicitly apply frequency selective damping and phase shift to the frequency response. Alfonso teaches the acoustic characteristics are values that are added to the point definition, and may specify how different sound frequencies are affected when colliding with or coming into contact with the point cloud points that are defined with those acoustic characteristics. The sound effects defined by the acoustic characteristics may include specifying an amount by which certain frequencies are absorbed or reflected, adjustments to apply to different frequencies, adding echo, reverberation, distortion, changing tone, timbre adjustments, amplitude adjustments, loudness adjustments, and/or specifying other changes to the sound or sound properties (col. 13, lines 11-22).
As to claim 16, Alfonso teaches the method of claim 15, wherein one or more acoustic effects is selected from one or more of phase advance, an amplitude level, and a decay interval (col. 13, lines 11-22 - the acoustic characteristics are values that are added to the point definition, and may specify how different sound frequencies are affected when colliding with or coming into contact with the point cloud points that are defined with those acoustic characteristics. The sound effects defined by the acoustic characteristics may include specifying an amount by which certain frequencies are absorbed or reflected, adjustments to apply to different frequencies, adding echo, reverberation, distortion, changing tone, timbre adjustments, amplitude adjustments, loudness adjustments, and/or specifying other changes to the sound or sound properties).
Claims 17, 19, 20 are rejected for the same reasons discussed above with respect to claims 10, 11, 12, respectively.
As to claim 18, Reams teaches the method of claim 17, further comprising: producing the audio signal output from a model of the AI network, the model trained to produce an audio sample that is pleasing to the human ear ([0038] - a 10-second sample is required in order to train certain artificial intelligence components, then sample selection system 204 can allow the user to listen to the sample audio data to determine whether the aesthetic characteristics are desirable).
9. Claim 21 is rejected under 35 U.S.C. 103 as being unpatentable over Matsunaga and/or Iwase in view of Qian (2025/0377424).
As to claim 21, Matsunaga teaches the audio synthesizing device of claim 1, wherein delay circuits 17R-L, 18R-L, 19R-L for receiving a frequency response derived from the excitation of the plurality of resonator circuits (Fig. 3 – with the output from the corresponding groups 1, 2, or 3) and applying one or more acoustic effects ([0021-0022] – with the stereo delay effect) to selected frequencies from the frequency response ([0039-0040] – with the delay applied by circuits 17R, 17L to resonance circuits of key group 1; hence it would have been obvious corresponding to selected frequencies of keys belonging to group 1 generated by the plurality of resonator circuits (Fig. 3, resonators). Matsunaga does not explicitly discuss outputting a component signal as one component of a raw output signal of the plurality of resonator circuits wherein the excitation signal is selected to produce a particular baseline for the raw output signal of the plurality of resonator circuits.
Qian teaches resonator circuits 50 ([0080]), simultaneously retrieve EEG signals, the derivatized phase signal dØ.sub.t/dt was low pass filtered, leading to raw EEG signal in FIG. 11F containing repetitive baseline variation pattern that was synchronized with individual slice acquisition ([0126]).
It would have been obvious before the effective filing date of the claimed invention to incorporate the teachings of Qian into the teachings of Matsunaga for the purpose of electing an excitation signal to produce a particular baseline for the raw output signal is driven by several key performance and design objectives.
Response to Arguments
10. Applicant’s arguments with respect to claims 1-21 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
11. Any inquiry concerning this communication or earlier communications from the examiner should be directed to QUYNH H NGUYEN whose telephone number is (571)272-7489. The examiner can normally be reached Monday-Thursday 7:30AM-5:30PM.
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/QUYNH H NGUYEN/Primary Examiner, Art Unit 2693
