	US 12,299,718 B1
	Customizable voice messaging platform
Eric Johnson, Dallas, TX (US); Patrick Williamson, Atlanta, GA (US); and Chad Nickell, Siler City, NC (US)
Assigned to Robin Voice, Inc., Dallas, TX (US)
Filed by Robin Voice, Inc., Dallas, TX (US)
Filed on Jan. 28, 2025, as Appl. No. 19/039,743.
Claims priority of provisional application 63/733,572, filed on Dec. 13, 2024.
Claims priority of provisional application 63/718,902, filed on Nov. 11, 2024.
Claims priority of provisional application 63/548,703, filed on Feb. 1, 2024.
Int. Cl. G06Q 30/0241 (2023.01); G06Q 30/0251 (2023.01); G06T 11/00 (2006.01); G10L 15/18 (2013.01); G10L 15/183 (2013.01); G10L 21/14 (2013.01); G10L 25/18 (2013.01)

CPC G06Q 30/0276 (2013.01) [G06Q 30/0269 (2013.01); G06T 11/00 (2013.01); G10L 15/1815 (2013.01); G10L 15/183 (2013.01); G10L 21/14 (2013.01); G10L 25/18 (2013.01)]

20 Claims

1. A computer-implemented method for generating a customized message for a target, the computer-implemented method comprising:

accessing a script comprising one or more tokens;

generating a request for a first user input of a first parameter value for a first parameter by a user;

when the user provides the first user input of the first parameter value, assigning the first user input as the first parameter value of the first parameter;

when the user does not provide the first user input of the first parameter value, assigning a default first parameter value as the first parameter value of the first parameter;

generating a request for a first machine learning model to generate an audio template using at least the script and the first parameter value;

providing the request to the first machine learning model, wherein providing the request to the first machine learning model causes generation of the audio template by the first machine learning model;

accessing the audio template;

identifying a timestamp of a token in the audio template;

determining a duration of the token in the audio template;

determining a token value for the target;

generating a second request for a second machine learning model to generate an audio representation of the token value, wherein the second request includes at least the token value, an indication of a portion of the audio template preceding the token, and an indication of a portion of the audio template following the token;

generating, using a second machine learning model, an audio representation of the token value;

determining a length of the audio representation of the token value;

adjusting a duration of the token in the audio template based on the length of the audio representation of the token value;

inserting the audio representation of the token value into the audio template;

generating a graphical representation based on a graphic information provided by the user, wherein the graphic information comprises one or more of: a background color, a foreground color, a logo, or an image;

generating the customized message using the audio representation and the graphical representation; and

causing delivery of the customized message to the target via a first delivery channel.