# US 2024/0202984 A1 · Systems and methods for generating images to achieve a style

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- Number: US 2024/0202984 A1
- Document ID: US20240202984A1
- Status: Published application
- Kind: A1
- Application number: 18/083,456
- Filed: 2022-12-16
- Published: 2024-06-20
- Earliest claimed: 2022-12-16
- Assignees: Sony Interactive Entertainment Inc.
- Applicants: Sony Interactive Entertainment Inc.
- Inventors: Arran Green; Celeste Bean; Michael Taylor
- Web page: https://patentgrep.com/patent/US20240202984A1

## CPC

- G06F 16/535: Filtering based on additional data, e.g. user or group profiles
- G06T 11/00: Two-dimensional [2D] image generation
- G06F 3/013: {Eye tracking input arrangements (G06F3/015 takes precedence)}
- G06F 16/583: using metadata automatically derived from the content
- G06F 40/166: Editing, e.g. inserting or deleting
- G06F 40/284: Lexical analysis, e.g. tokenisation or collocates
- G06N 3/02: Neural networks
- G10L 15/1807: {using prosody or stress}
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G10L: SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING

## Abstract

A method generating an image according to a style is described. The method includes receiving a textual description describing a first image. The method further includes applying an artificial intelligence (AI) model to determine the style of a second image based on the textual description, the first image, a plurality of descriptions, and a plurality of images to generate a suggestion. The style provides a context to the second image. The style is lacking in the first image. The method includes generating the second image with the suggestion according to the style and providing the second image to a client device for display.

## Claims

### Claim 1

A method generating an image according to a style, comprising:
receiving a textual description describing a first image;
applying an artificial intelligence (AI) model to determine the style of a second image based on the textual description, the first image, a plurality of descriptions, and a plurality of images to generate a suggestion, wherein the style provides a context to the second image, wherein the style is lacking in the first image;
generating the second image with the suggestion according to the style; and
providing the second image to a client device for display.

### Claim 2 (depends on 1)

The method of claim 1, wherein said applying the AI model includes:
identifying each word of the textual description as belonging to a first lexical category or a second lexical category; and
assigning a weight to said each word of the textual description according to the first lexical category or the second category; and
determining the style based on the weight.

### Claim 3 (depends on 1)

The method of claim 1, wherein said applying the AI model includes:
identifying two or more words of the textual description as belonging the same one of a plurality of lexical categories;
identifying locations of the two or more words in the textual description; and
assigning weights to the two or more words based on the locations; and
determining the style based on the weights.

### Claim 4 (depends on 1)

The method of claim 1, wherein said applying the AI model includes:
identifying each word of the textual description as being esoteric or exoteric; and
assigning a weight to said each word of the textual description based on whether the word is esoteric or exoteric; and
determining the style based on the weight.

### Claim 5 (depends on 1)

The method of claim 1, wherein said applying the AI model includes:
identifying a plurality of gaze directions of a user from whom the textual description is received; and
assigning weights to two or more words of the textual description based on the plurality of gaze directions; and
determining the style based on the weights.

### Claim 6 (depends on 1)

The method of claim 1, wherein said applying the AI model includes:
identifying amounts of emphasis by one or more users on audio data describing the textual description; and
assigning weights to two or more words of the textual description based on the amounts of emphasis; and
determining the style based on the weights.

### Claim 7 (depends on 1)

The method of claim 1, wherein said applying the AI model includes:
identifying amounts of input variables used for inputting the textual description; and
assigning weights to two or more words of the textual description based on the amounts of input variables; and
determining the style based on the weights.

### Claim 8 (depends on 1)

The method of claim 1, wherein the suggestion is a textual description.

### Claim 9 (depends on 1)

The method of claim 1, wherein the suggestion includes a reordering of words of the textual description, or a reduction in a number of the words of the textual description, or a combination thereof.

### Claim 10 (depends on 1)

The method of claim 1, further comprising:
providing the suggestion to the client device;
receiving a response to the suggestion, wherein the response indicates an acceptance or a denial of the suggestion.

### Claim 11

A server system for customizing an image based on user preferences, comprising:
a processor configured to:
receive a textual description describing a first image;
apply an artificial intelligence (AI) model to determine a style of a second image based on the textual description, the first image, a plurality of descriptions, and a plurality of images to generate a suggestion, wherein the style provides a context to the second image, wherein the style is lacking in the first image;
generate the second image with the suggestion according to the style; and
provide the second image to a client device for display; and
a memory device coupled to the processor.

### Claim 12 (depends on 11)

The server system of claim 11, wherein to apply the AI model, the processor is configured to:
identify each word of the textual description as belonging to a first lexical category or a second lexical category; and
assign a weight to said each word of the textual description according to the first lexical category or the second category; and
determine the style based on the weight.

### Claim 13 (depends on 11)

The server system of claim 11, wherein to apply the AI model, the processor is configured to:
identify two or more words of the textual description as belonging the same one of a plurality of lexical categories;
identify locations of the two or more words in the textual description; and
assign weights to the two or more words based on the locations; and
determine the style based on the weights.

### Claim 14 (depends on 11)

The server system of claim 11, wherein to apply the AI model, the processor is configured to:
identify each word of the textual description as being esoteric or exoteric; and
assign a weight to said each word of the textual description based on whether the word is esoteric or exoteric; and
determine the style based on the weight.

### Claim 15 (depends on 11)

The server system of claim 11, wherein to apply the AI model, the processor is configured to:
identify a plurality of gaze directions of a user from whom the textual description is received; and
assign weights to two or more words of the textual description based on the plurality of gaze directions; and
determine the style based on the weights.

### Claim 16 (depends on 11)

The server system of claim 11, wherein to apply the AI model, the processor is configured to:
identify amounts of emphasis by one or more users on audio data describing the textual description; and
assign weights to two or more words of the textual description based on the amounts of emphasis; and
determine the style based on the weights.

### Claim 17 (depends on 11)

The server system of claim 11, wherein to apply the AI model, the processor is configured to:
identify amounts of input variables used for inputting the textual description; and
assign weights to two or more words of the textual description based on the amounts of input variables; and
determine the style based on the weights.

### Claim 18

A non-transitory computer-readable medium containing program instructions for generating an image according to a style, wherein execution of the program instructions by one or more processors of a computer system causes the one or more processors to carry out operations of:
receiving a textual description describing a first image;
applying an artificial intelligence (AI) model to determine the style of a second image based on the textual description, the first image, a plurality of descriptions, and a plurality of images to generate a suggestion, wherein the style provides a context to the second image, wherein the style is lacking in the first image;
generating the second image with the suggestion according to the style; and
providing the second image to a client device for display.

### Claim 19 (depends on 18)

The non-transitory computer-readable medium of claim 18, wherein the operation of applying the AI model includes:
identifying each word of the textual description as belonging to a first lexical category or a second lexical category; and
assigning a weight to said each word of the textual description according to the first lexical category or the second category; and
determining the style based on the weight.

### Claim 20 (depends on 18)

The non-transitory computer-readable medium of claim 18, wherein the operation of applying the AI model includes:
identifying two or more words of the textual description as belonging the same one of a plurality of lexical categories;
identifying locations of the two or more words in the textual description; and
assigning weights to the two or more words based on the locations; and
determining the style based on the weights.