18391536. RECOGNIZING POLLING QUESTIONS FROM A CONFERENCE CALL DISCUSSION simplified abstract (GOOGLE LLC)
Contents
- 1 RECOGNIZING POLLING QUESTIONS FROM A CONFERENCE CALL DISCUSSION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 RECOGNIZING POLLING QUESTIONS FROM A CONFERENCE CALL DISCUSSION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 How does the machine learning model handle different accents and speech patterns among participants?
- 1.11 What measures are in place to ensure the privacy and security of the data collected during the conference calls?
- 1.12 Original Abstract Submitted
RECOGNIZING POLLING QUESTIONS FROM A CONFERENCE CALL DISCUSSION
Organization Name
Inventor(s)
Emily Burd of New York NY (US)
Akshat Sharma of Cambridge MA (US)
RECOGNIZING POLLING QUESTIONS FROM A CONFERENCE CALL DISCUSSION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18391536 titled 'RECOGNIZING POLLING QUESTIONS FROM A CONFERENCE CALL DISCUSSION
Simplified Explanation
The patent application describes a method where verbal phrases provided by participants during a conference call are used as input for a machine learning model. The model generates outputs, from which polling questions are extracted to be used for polling participants during the call.
- Verbal phrases from participants are input into a machine learning model.
- Outputs from the model are used to generate polling questions for participants.
- The polling questions are based on the verbal input from participants.
Potential Applications
This technology could be applied in various industries such as market research, customer feedback analysis, and employee engagement surveys.
Problems Solved
This technology streamlines the process of gathering feedback and opinions from participants during conference calls, making it more efficient and structured.
Benefits
The benefits of this technology include improved data collection, better engagement with participants, and more effective decision-making based on the feedback received.
Potential Commercial Applications
A potential commercial application of this technology could be in the development of software tools for virtual meetings and conference calls, enhancing the overall experience for participants.
Possible Prior Art
One possible prior art could be the use of machine learning models for analyzing speech patterns and generating questions based on verbal input, although the specific application to conference calls may be novel.
Unanswered Questions
How does the machine learning model handle different accents and speech patterns among participants?
The article does not address how the machine learning model accounts for variations in speech patterns and accents, which could impact the accuracy of the generated polling questions.
What measures are in place to ensure the privacy and security of the data collected during the conference calls?
The article does not mention any specific security protocols or privacy measures implemented to protect the data collected from participants during the conference calls.
Original Abstract Submitted
Data indicating one or more verbal phrases provided by one or more participants during a conference call is fed as input to a machine learning model. One or more outputs of the machine learning model are obtained. A polling question for polling at least a portion of the participants is extracted from the one or more outputs of the machine learning model. The polling question is based on one or more verbal phrases provided by the one or more participants. The polling question is provided for polling the at least the portion of the participants during the conference call.
