Systems and methods to improve trust in conversations

US12412562B2 · kind B2 · utility

Assignee

• ACCENTURE GLOBAL SOLUTIONS LIMITED · IE

Inventors

• Lan Guan · New York, US
• Neeraj D Vadhan · Los Altos, US
• Guanglei Xiong · Pleasanton, US
• Anwitha Paruchuri · San Jose, US
• Sukryool Kang · Dublin, US
• Sujeong Cha · Manhattan, US
• Anupam Anurag Tripathi · Chicago, US
• Thomas Wayne Hancock · Oklahoma City, US
• Jill Gengelbach-Wylie · Austin, US
• Jayashree Subrahmonia · San Jose, US

Key dates

• Filing date: Apr 29, 2022
• Grant date: Sep 9, 2025
• Expiry date: Dec 31, 2043

Classification

• Technology area (CPC G): Physics
• CPC primary: G10L2021/105
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

The present disclosure relates to a system, a method, and a product for using machine learning models to quantify and/or improve trust in conversations. The system includes a non-transitory memory; and a processor in communication with the non-transitory memory. The processor executes the instructions to cause the system to: obtain a set of vocal features and a set of text features for each sample in audio samples; obtain a trust score for each sample; perform a preprocess to obtain a set of input features for each sample; determine a type of machine-learning algorithm for the machine-learning network; tune a set of hyper parameters for the machine-learning network; generate a predicated trust score by the machine-learning network with the sets of input features for each sample; and train the machine-learning network based on the predicated trust score and the trust score for each sample to obtain the training result.