Apple inc. (20240105079). Interactive Reading Assistant simplified abstract
Contents
- 1 Interactive Reading Assistant
Interactive Reading Assistant
Organization Name
Inventor(s)
Barry-John Theobald of Sunnyvale CA (US)
Russell Y. Webb of San Jose CA (US)
Nicholas Elia Apostoloff of San Jose CA (US)
Interactive Reading Assistant - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240105079 titled 'Interactive Reading Assistant
Simplified Explanation
The abstract describes a method for assessing a user's speech proficiency value and providing training text based on the proficiency level. The method involves obtaining speech data, analyzing linguistic features, and adjusting operational values of a speech classifier.
- Obtaining a speech proficiency value indicator for a user of an electronic device
- Displaying training text based on the user's proficiency level
- Obtaining speech data associated with the training text
- Analyzing linguistic features within the speech data using a speech classifier
- Adjusting operational values of the speech classifier based on the analysis and the proficiency value
Potential Applications
This technology could be applied in language learning apps, speech therapy tools, and virtual language tutors.
Problems Solved
This technology helps users improve their speech proficiency by providing tailored training based on their current proficiency level.
Benefits
Users can enhance their language skills in a personalized and efficient manner, leading to better communication abilities.
Potential Commercial Applications
"Enhancing Language Learning with Speech Proficiency Assessment Technology"
Possible Prior Art
One possible prior art could be speech recognition software that adapts to users' speech patterns to improve accuracy over time.
Unanswered Questions
How does this technology handle different accents and dialects in speech data?
The method described in the abstract focuses on linguistic features within speech data, but it is unclear how it accounts for variations in accents and dialects.
What is the accuracy rate of the speech classifier in determining speech proficiency levels?
The abstract mentions adjusting operational values of the speech classifier based on analysis, but it does not specify the accuracy rate of the classifier in determining proficiency levels.
Original Abstract Submitted
a method includes obtaining a speech proficiency value indicator indicative of a speech proficiency value associated with a user of the electronic device. the method further includes in response to determining that the speech proficiency value satisfies a threshold proficiency value: displaying training text via the display device; obtaining, from the audio sensor, speech data associated with the training text, wherein the speech data is characterized by the speech proficiency value; determining, using a speech classifier, one or more speech characterization vectors for the speech data based on linguistic features within the speech data; and adjusting one or more operational values of the speech classifier based on the one or more speech characterization vectors and the speech proficiency value.
