Invention Publication
- Patent Title: GENERATING ENCODED TEXT BASED ON SPOKEN UTTERANCES USING MACHINE LEARNING SYSTEMS AND METHODS
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Application No.: US18414095Application Date: 2024-01-16
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Publication No.: US20240152684A1Publication Date: 2024-05-09
- Inventor: Peter P. Myron , Michael Mitchell
- Applicant: T-Mobile USA, Inc.
- Applicant Address: US WA Bellevue
- Assignee: T-Mobile USA, Inc.
- Current Assignee: T-Mobile USA, Inc.
- Current Assignee Address: US WA Bellevue
- Main IPC: G06F40/126
- IPC: G06F40/126 ; G06F40/166 ; G06N20/00 ; G10L15/22

Abstract:
Systems and methods for generating encoded text representations of spoken utterances are disclosed. Audio data is received for a spoken utterance and analyzed to identify a nonverbal characteristic, such as a sentiment, a speaking rate, or a volume. An encoded text representation of the spoken utterance is generated, comprising a text transcription and a visual representation of the nonverbal characteristic. The visual representation comprises a geometric element, such as a graph or shape, or a variation in a text attribute, such as font, font size, or color. Analysis of the audio data and/or generation of the encoded text representation can be performed using machine learning.
Public/Granted literature
- US12248748B2 Generating encoded text based on spoken utterances using machine learning systems and methods Public/Granted day:2025-03-11
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