https://bugs.documentfoundation.org/show_bug.cgi?id=155679
--- Comment #2 from Ramez <[email protected]> --- (In reply to Heiko Tietze from comment #1) > Fantastic idea. Besides the integration part, which I think should be done > per extension, it will be a challenge to analyze the data. For example the > speaking pace depends first of all largely on the language and secondly > needs to be translated into maybe number and length of breaks that could > then become some kind of percentage. The same is true for the other quality > measures: very difficult to measure, evaluate, and norm. Thank you for your feedback and interest in my feature suggestion. I agree that the integration part should be done per extension, as different presentation or meeting platforms may have different requirements and formats. As for the data analysis part, I think that there are some possible solutions for the challenges that you have mentioned. For example: - For the speaking pace, a relative measure that compares the user's speed with the optimal speed for their language and context could be used. Speech recognition or audio analysis tools could also be used to estimate the speaking pace and identify pauses and breaks. - For the other quality measures, existing models or frameworks that have been developed or validated by experts in communication, linguistics, psychology, or education could be used. Natural language processing or machine learning techniques could also be used to detect and classify the user's speech features and compare them with normative scores or standards. - For the feedback and suggestions part, best practices and guidelines that have been established or recommended by professional speakers, trainers, coaches, or educators could be used. Gamification or motivational elements could also be used to make the feedback more engaging and rewarding for the user. It is also possible to learn from how Microsoft has developed the Speaker Coach feature for both Teams and PowerPoint, and how they have solved some of the issues and challenges that you raised. They have used a combination of speech analysis, natural language processing, machine learning, linguistic resources, user interface design, gamification, and data visualization techniques to provide feedback on the user's speaking skills and a summary report with statistics and recommendations. I hope this gives you some idea of how this feature could be developed in LibreOffice. I would love to hear your thoughts or suggestions on how to do that. Thank you for your collaboration. -- You are receiving this mail because: You are the assignee for the bug.
