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 .
Application Status
This office action is responsive to the Application No.:18/630,071, filed on 04/09/2024 (Foreign Priority Date: 08/29/2019).
Claims 1-20 are pending and presented for examination.
This action has been made NON-FINAL.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 04/09/2024 is being considered by the examiner. A signed IDS is hereby attached.
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 1-20 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.
Claims 1, 11 and 14 recites “determining linguistics information corresponding to a speech frame in the first speech, the linguistics information being used for identifying a distribution possibility that the speech frame in the first speech pertains to phonemes regardless of a speaker of the first speech and a text corresponding to a content in the speech frame” and “determining an expression parameter corresponding to the speech frame in the first speech according to the linguistics information.” However, this claim limitation is silent in disclosing how the claim limitation is determined. Therefore, this claim is rendered as indefinite.
Claims 1, 11 and 14 recites “being used for”. The use of the term “used for” can be interpreted as intended use and therefore these claims are rendered as indefinite.
Claims 1, 11 and 14 recite “possibility”. It is not clear to the examiner if the term “possibility” is an optional claim limitation or if "possibility" should be interpreted as a definite statement. Therefore, these claims are rendered as indefinite.
Claims 2, 5, 7, 8, 9, 12, 15, 18 and 20 recites “determining”. However, the claims are silent in disclosing how the claim limitation is determined. Therefore, the claims are rendered as indefinite.
The dependent claims are rejected for depending upon a rejected base claim.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Independent claims 1, 11 and 14 of the instant application are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 11 and 14 (respectively) of Kang et al (U.S. Patent No. 12,002,138) since the claims, if allowed, would improperly extend the "right to exclude" already granted in the patent.
INSTANT APPLICATION
Kang et al. US 12,002,138
A speech-driven animation method, performed by an audio and video processing device, the method comprising: obtaining a first speech, the first speech comprising a plurality of speech frames; determining linguistics information corresponding to a speech frame in the first speech, the linguistics information being used for identifying a distribution possibility that the speech frame in the first speech pertains to phonemes regardless of a speaker of the first speech and a text corresponding to a content in the speech frame; determining an expression parameter corresponding to the speech frame in the first speech according to the linguistics information; and enabling, according to the expression parameter, an animation character to make an expression corresponding to the first speech.
1. A speech-driven animation method, performed by an audio and video processing device, the method comprising: obtaining a first speech with an acoustic feature, the first speech comprising a plurality of speech frames; determining linguistics information corresponding to a speech frame in the first speech by applying a neural network mapping model to extract the acoustic feature, the linguistics information being used for identifying a distribution possibility that the speech frame in the first speech pertains to phonemes; determining an expression parameter corresponding to the speech frame in the first speech according to the linguistics information, wherein the expression parameters do not reflect pronunciation habits of different speakers; and enabling, according to the expression parameter, an animation character to make an expression corresponding to the first speech.
11. A speech-driven animation apparatus, deployed on an audio and video processing device, the apparatus comprising a processor and a memory, the memory being configured to store program code and transmit the program code to the processor; and when executing the program code, the processor being configured to: obtain a first speech, the first speech comprising a plurality of speech frames; determine linguistics information corresponding to a speech frame in the first speech, the linguistics information being used for identifying a distribution possibility that the speech frame in the first speech pertains to phonemes regardless of a speaker of the first speech and a text corresponding to a content in the speech frame; determine an expression parameter corresponding to the speech frame in the first speech according to the linguistics information; and enable according to the expression parameter, an animation character to make an expression corresponding to the first speech
11. A speech-driven animation apparatus, deployed on an audio and video processing device, the apparatus comprising a processor and a memory, the memory being configured to store program code and transmit the program code to the processor; and when executing the program code, the processor being configured to: obtain a first speech with an acoustic feature, the first speech comprising a plurality of speech frames; determine linguistics information corresponding to a speech frame in the first speech by applying a neural network mapping model to extract the acoustic feature, the linguistics information being used for identifying a distribution possibility that the speech frame in the first speech pertains to phonemes; determine an expression parameter corresponding to the speech frame in the first speech according to the linguistics information, wherein the expression parameters do not reflect pronunciation habits of different speakers; and enable according to the expression parameter, an animation character to make an expression corresponding to the first speech.
14. A non-transitory computer-readable storage medium, configured to store program code, the program code, when being executed by a processor, causing the processor to perform: obtaining a first speech, the first speech comprising a plurality of speech frames; determining linguistics information corresponding to a speech frame in the first speech, the linguistics information being used for identifying a distribution possibility that the speech frame in the first speech pertains to phonemes regardless of a speaker of the first speech and a text corresponding to a content in the speech frame; determining an expression parameter corresponding to the speech frame in the first speech according to the linguistics information; and enabling, according to the expression parameter, an animation character to make an expression corresponding to the first speech.
14. A non-transitory computer-readable storage medium, configured to store program code, the program code, when being executed by a processor, causing the processor to perform: obtaining a first speech with an acoustic feature, the first speech comprising a plurality of speech frames; determining linguistics information corresponding to a speech frame in the first speech by applying a neural network mapping model to extract the acoustic feature, the linguistics information being used for identifying a distribution possibility that the speech frame in the first speech pertains to phonemes; determining an expression parameter corresponding to the speech frame in the first speech according to the linguistics information, wherein the expression parameters do not reflect pronunciation habits of different speakers; and enabling, according to the expression parameter, an animation character to make an expression corresponding to the first speech.
Although the claims at issue are not identical, they are not patentably distinct from each other because as shown above, claims 1, 11 and 14 of Kang et al (U.S. Patent No. 12,002,138) contains every element of claims 1, 11 and 14 of the instant application and as such anticipates claims 1, 11 and 14 of the instant application.
“A later application claim is not patentably distinct from an earlier patent claim if the later claim is obvious over, or anticipated by, the earlier claim. In re Longi, 759 F.2d at 896, 225 USPQ at 651 (affirming a holding of obviousness-type double patenting because the claims at issue were obvious over claims in four prior art patents); In re Berg, 140 F.3d at 1437, 46 USPQ2d at 1233 (Fed. Cir. 1998) (affirming a holding of obviousness-type double patenting where a patent application claim to a genus is anticipated by a patent claim to a species within that genus).” ELI LILLY AND COMPANY v BARR LABORATORIES, INC., United States Court of Appeals for the Federal Circuit, ON PETITION FOR REHEARING EN BANC (DECIDED: May 30, 2001).
Claim Rejections - 35 USC § 103
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.
Claim(s) 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Miller, US 20190005021 in view of Latorre-Martinez, US 9959657.
Claim 1:
Miller discloses a speech-driven animation method, performed by an audio and video processing device (See Miller Abstract; Paragraphs 0049-0053; 0060). Miller failed to explicitly disclose the following:
obtaining a first speech, the first speech comprising a plurality of speech frames;
determining linguistics information corresponding to a speech frame in the first speech, the linguistics information being used for identifying a distribution possibility that the speech frame in the first speech pertains to phonemes regardless of a speaker of the first speech and a text corresponding to a content in the speech frame
However, Latorre-Martinez discloses the above-mentioned claim limitations in Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have further modified Miller by the teachings of Latorre-Martinez to incorporate linguistics information pertaining to phonemes enable improved computer-generated animated head, more effectively (See Latorre-Martinez Field of Invention section).
As modified:
The combination of Miller and Latorre-Martinez discloses the following:
obtaining a first speech, the first speech comprising a plurality of speech frames (See Latorre-Martinez Column 28, Lines 39-451);
determining linguistics information (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-502) corresponding to a speech frame in the first speech (See Latorre-Martinez Column 28, Lines 39-453), the linguistics information (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-504) being used for identifying a distribution possibility that the speech frame in the first speech pertains to phonemes regardless of a speaker of the first speech (See Latorre-Martinez Column 28, Lines 39-455) and a text corresponding to a content in the speech frame (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-506);
determining an expression parameter (See Miller Paragraphs 0094-0095; 0097) corresponding to the speech frame in the first speech according to the linguistics information (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-507);
and enabling, according to the expression parameter (See Miller Paragraphs 0094-0095; 0097), an animation character (See Miller Paragraphs 0049-0053; 00608) to make an expression (See Miller Paragraph 00529) corresponding to the first speech (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-5010).
Claim 2:
The combination of Miller and Latorre-Martinez discloses wherein a target speech frame is a speech frame in the first speech (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50), and the determining an expression parameter (See Miller Paragraphs 0094-0095; 0097) corresponding to the speech frame in the first speech according to the linguistics information (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50) comprises: determining a speech frame set in which the target speech frame is located (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50), the speech frame set comprising the target speech frame and speech frames preceding and succeeding the target speech frame (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50); and determining an expression parameter (See Miller Paragraphs 0094-0095; 0097) corresponding to the target speech frame according to linguistics information (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50) corresponding to each speech frame in the speech frame set (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50).
Claim 3:
The combination of Miller and Latorre-Martinez discloses wherein a quantity of speech frames (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50) in the speech frame set is determined according to a neural network mapping model, or a quantity of speech frames in the speech frame set is determined according to a speech segmentation result of the first speech (See Miller Paragraph 0096).
Claim 4:
The combination of Miller and Latorre-Martinez discloses wherein the speech frames preceding (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50) and succeeding the target speech frame are consecutive preceding and succeeding speech frames, or the speech frames preceding and succeeding the target speech frame are inconsecutive speech frames (See Latorre-Martinez Column 28, Lines 39-45).
Claim 5:
The combination of Miller and Latorre-Martinez discloses wherein the determining an expression parameter (See Miller Paragraphs 0094-0095; 0097) corresponding to the target speech frame according to linguistics information (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50) corresponding to each speech frame in the speech frame set comprises: determining an undetermined expression parameter (See Miller Paragraphs 0094-0095; 0097) corresponding to each speech frame in the speech frame set according to the linguistics information corresponding to each speech frame in the speech frame set (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50); and calculating the expression parameter (See Latorre-Martinez Column 29, Lines 34-40) corresponding to the target speech frame according to undetermined expression parameters (See Miller Paragraphs 0094-0095; 0097) of the target speech frame that are respectively determined in different speech frame sets (See Latorre-Martinez Column 28, Lines 39-45).
Claim 6:
The combination of Miller and Latorre-Martinez discloses wherein the linguistics information (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50) comprises any one or a combination of two or more of a phonetic posterior gram (PPG), a bottleneck feature, and an embedding feature (See Miller Paragraphs 0032; 0101-0102).
Claim 7:
The combination of Miller and Latorre-Martinez discloses wherein the determining an expression parameter (See Miller Paragraphs 0094-0095; 0097) corresponding to the speech frame in the first speech according to the linguistics information (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50) comprises: determining the expression parameter (See Miller Paragraphs 0094-0095; 0097) corresponding to the speech frame in the first speech according to the linguistics information by using the neural network mapping model, the neural network mapping model comprising a deep neural network (DNN) model, a long short-term memory (LSTM) model, or a bidirectional long short-term memory (BLSTM) model (See Miller Paragraph 0096).
Claim 8:
The combination of Miller and Latorre-Martinez discloses wherein the determining an expression parameter (See Miller Paragraphs 0094-0095; 0097) corresponding to the speech frame (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32) in the first speech according to the linguistics information (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50) comprises: determining the expression parameter (See Miller Paragraphs 0094-0095; 0097) corresponding to the speech frame in the first speech according to the linguistics information (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50) and a sentiment vector corresponding to the first speech (See Miller Paragraph 0053; 0057; 0107; 0167).
Claim 9:
The combination of Miller and Latorre-Martinez discloses wherein the determining linguistics information (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50) corresponding to a speech frame in the first speech (See Miller Paragraphs 0049-0053; 0096; 0190) comprises: determining an acoustic feature corresponding to the speech frame in the first speech (See Miller Paragraphs 0049-0053; 0096; 0190); and determining linguistics information (See Latorre-Martinez Column 2, Lines 60-67; Column 6, Lines 5-32; Column 10, Lines 36-50) corresponding to the acoustic feature by using an automatic speech recognition (ASR) model (See Miller Paragraph 0096).
Claim 10:
The combination of Miller and Latorre-Martinez discloses wherein the ASR model is obtained through training according to training samples that comprise correspondences between speech segments and phonemes (See Miller Paragraph 0096).
Claims 11-13:
Claims 11-13 are rejected on the same basis as claims 1-3.
Claims 14-20:
Claims 14-20 are rejected on the same basis as claims 1-7.
Pertinent Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20030220798 relates to a user interface that provides a user with feedback as to the status of a voice recognition process. More particularly, the present invention provides a user interface that indicates when a voice recognition process identifies volume events, and then subsequently indicates when the voice recognition process recognizes those volume events.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHEREE N BROWN whose telephone number is (571)272-4229. The examiner can normally be reached M-F 5:30-2:00 PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, SAID BROOME can be reached at (571) 272-2931. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SHEREE N BROWN/Primary Examiner, Art Unit 2612 April 1, 2026
1 Latorre-Martinez Column 28, Lines 39-45 recites “The data is selected so that it is possible to select a set of frames from the training images which correspond to a set of common phonemes in each of the emotions. In some embodiments, about 7000 training sentences are used. However, much of this data is used to train the speech model to produce the speech vector as previously described.”
2 Latorre-Martinez Column 10, Lines 36-50 recites “The face characteristic independent means are clustered. In an embodiment, each cluster comprises at least one decision tree, the decisions used in said trees are based on linguistic, phonetic and prosodic variations. In an embodiment, there is a decision tree for each component which is a member of a cluster. Prosodic, phonetic, and linguistic contexts affect the facial gesture. Phonetic contexts typically affects the position and movement of the mouth, and prosodic (e.g. syllable) and linguistic (e.g., part of speech of words) contexts affects prosody such as duration (rhythm) and other parts of the face, e.g., the blinking of the eyes. Each cluster may comprise one or more sub-clusters where each sub-cluster comprises at least one of the said decision trees.”
3 Latorre-Martinez Column 28, Lines 39-45 recites “The data is selected so that it is possible to select a set of frames from the training images which correspond to a set of common phonemes in each of the emotions. In some embodiments, about 7000 training sentences are used. However, much of this data is used to train the speech model to produce the speech vector as previously described.”
4 Latorre-Martinez Column 10, Lines 36-50 recites “The face characteristic independent means are clustered. In an embodiment, each cluster comprises at least one decision tree, the decisions used in said trees are based on linguistic, phonetic and prosodic variations. In an embodiment, there is a decision tree for each component which is a member of a cluster. Prosodic, phonetic, and linguistic contexts affect the facial gesture. Phonetic contexts typically affects the position and movement of the mouth, and prosodic (e.g. syllable) and linguistic (e.g., part of speech of words) contexts affects prosody such as duration (rhythm) and other parts of the face, e.g., the blinking of the eyes. Each cluster may comprise one or more sub-clusters where each sub-cluster comprises at least one of the said decision trees.”
5 Latorre-Martinez Column 28, Lines 39-45 recites “The data is selected so that it is possible to select a set of frames from the training images which correspond to a set of common phonemes in each of the emotions. In some embodiments, about 7000 training sentences are used. However, much of this data is used to train the speech model to produce the speech vector as previously described.”
6 Latorre-Martinez Column 10, Lines 36-50 recites “The face characteristic independent means are clustered. In an embodiment, each cluster comprises at least one decision tree, the decisions used in said trees are based on linguistic, phonetic and prosodic variations. In an embodiment, there is a decision tree for each component which is a member of a cluster. Prosodic, phonetic, and linguistic contexts affect the facial gesture. Phonetic contexts typically affects the position and movement of the mouth, and prosodic (e.g. syllable) and linguistic (e.g., part of speech of words) contexts affects prosody such as duration (rhythm) and other parts of the face, e.g., the blinking of the eyes. Each cluster may comprise one or more sub-clusters where each sub-cluster comprises at least one of the said decision trees.”
7 Latorre-Martinez Column 10, Lines 36-50 recites “The face characteristic independent means are clustered. In an embodiment, each cluster comprises at least one decision tree, the decisions used in said trees are based on linguistic, phonetic and prosodic variations. In an embodiment, there is a decision tree for each component which is a member of a cluster. Prosodic, phonetic, and linguistic contexts affect the facial gesture. Phonetic contexts typically affects the position and movement of the mouth, and prosodic (e.g. syllable) and linguistic (e.g., part of speech of words) contexts affects prosody such as duration (rhythm) and other parts of the face, e.g., the blinking of the eyes. Each cluster may comprise one or more sub-clusters where each sub-cluster comprises at least one of the said decision trees.”
8 Miller Paragraphs 0049-0053; 0060 recites “Other symbolic content may include emojis, emoticons, avatars, (animated and/or static) GIFs, or image data, and such. For example, users frequently include emojis and/or animated GIFs in content to convey concepts. Thus, “a natural language expression” may include any such symbolic content such as mathematical notation, emojis, emoticons, and GIFs. The various natural language processing (NLP) and natural language models, such as but not limited to content-substance, content-style, and response-generation models are enabled to analyze and generate content that includes such symbolic content.”
9 Miller Paragraph 0052 recites “generate natural language expressions.”
10 Latorre-Martinez Column 10, Lines 36-50 recites “The face characteristic independent means are clustered. In an embodiment, each cluster comprises at least one decision tree, the decisions used in said trees are based on linguistic, phonetic and prosodic variations. In an embodiment, there is a decision tree for each component which is a member of a cluster. Prosodic, phonetic, and linguistic contexts affect the facial gesture. Phonetic contexts typically affects the position and movement of the mouth, and prosodic (e.g. syllable) and linguistic (e.g., part of speech of words) contexts affects prosody such as duration (rhythm) and other parts of the face, e.g., the blinking of the eyes. Each cluster may comprise one or more sub-clusters where each sub-cluster comprises at least one of the said decision trees.”
Prosecution Insights