Apple has filed for a patent (number 20200312183) for an “interactive reading assistant” that will users, especially young ones, with reading on an Apple device such as an iPhone, iPad, or Mac.
In the patent filing, Apple notes that current voice detection systems are able to detect the presence of speech of a human user, and determine certain sounds (e.g., phonemes) and words within the detected speech. A variety of apps may be implemented based on the determined sounds and words. One of these applications is assisting a user (e.g., children or polyglots) in speaking (e.g., uttering) a particular language.
However, in some situations, Apple says that current voice detection systems aren’t equipped to effectively assist a user in reading. Current voice detection systems are unable to assess whether certain vocalizations (e.g., utterances) made by a user match corresponding expected values.
For example, a user with a physical condition or attribute, such as a speech impediment or an underdeveloped vocal tract, produces a type of vocalization that is reflective of the physical condition or attribute. A current voice detection system may have difficulty recognizing the type of vocalization. This means it can’t provide helpful feedback in order to aid proper reading (e.g., pronunciation) of known text content. As another example, content is sometimes too complex or not complex enough (e.g., dull or boring) to sufficiently engage a user to read. A user without useful feedback or an unengaged user ultimately spends more time to complete a particular language lesson, resulting in greater resource utilization (e.g., greater processing and memory utilization, reduced battery life, greater wear-and-tear, etc.). Apple says it would be useful to provide reading assistance in response to an assessment of a particular type of user vocalization, and in a manner that engages and/or encourages the user to read.
Here’s the summary of the patent filing: “A method includes displaying a first set of text content characterized by a first difficulty level. The method includes obtaining speech data associated with the first set of text content. The method includes determining linguistic feature(s) within the speech data. The method includes in response to completion of the speech data, determining a reading proficiency value associated with the first set of text content and based on the linguistic feature(s).
“The method includes in accordance with determining the reading proficiency value satisfies change criteria, changing a difficulty level for a second set of text content. After changing the difficulty level, the second set of text content corresponds to a second difficulty level different from the first difficulty level. The method includes in accordance with determining the reading proficiency value does not satisfy the change criteria, maintaining the second set of text content at the first difficulty level.”
