Google llc (20240119074). RECOGNIZING POLLING QUESTIONS FROM A CONFERENCE CALL DISCUSSION simplified abstract
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 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 20240119074 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 one or more outputs, from which a polling question is extracted to be used for polling at least a portion of the participants during the call.
- Verbal phrases from conference call participants are input into a machine learning model.
- The model generates outputs, from which a polling question is extracted.
- The polling question is based on the verbal phrases provided by participants and is used to poll at least a portion of the participants during the conference call.
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 a conference call, making it more efficient and structured.
Benefits
The benefits of this technology include improved data collection, real-time feedback analysis, and enhanced participant engagement during conference calls.
Potential Commercial Applications
A potential commercial application of this technology could be in the development of software tools for virtual meetings and conference calls, catering to businesses looking to enhance their communication and decision-making processes.
Possible Prior Art
One possible prior art could be the use of machine learning models for analyzing speech patterns and extracting meaningful insights from verbal data in various contexts.
Unanswered Questions
How does this technology ensure the privacy and confidentiality of participants' verbal data during the polling process?
The article does not address the specific measures or protocols in place to protect the privacy and confidentiality of participants' verbal data during the polling process. This is an important consideration, especially in industries where sensitive information may be discussed during conference calls.
What are the potential limitations or biases in the polling questions generated by the machine learning model?
The article does not discuss the potential limitations or biases that may arise in the polling questions generated by the machine learning model. It is essential to consider factors such as language nuances, cultural differences, and participant demographics that could impact the accuracy and relevance of the polling questions.
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.
