Systems and methods for grapheme-phoneme correspondence learning

A device for teaching grapheme-phoneme correspondence comprising

• a display configured to render a grapheme graphical user interface (GUI) that includes one or more graphemes for pronunciation by a human to teach the human a grapheme-phoneme correspondence;
• a speaker;
• a microphone configured to capture a sound made by the human for a select grapheme of the one or more graphemes displayed on the display and provide audio data;
• memory to store machine-readable instructions;
• and
• one or more processors to access the memory and execute the machine-readable instructions, the machine-readable instructions comprising:
• a trained machine learning (ML) model programmed to determine whether the sound made by the human corresponds to a phoneme for the selected grapheme displayed on the display based on the audio data;
• and
• a grapheme-phoneme module programmed to cause the speaker to output a sound representative of the phoneme for the grapheme displayed on the display in response to the trained ML model determining that the sound made by the human does not match the phoneme for the selected grapheme on the display corresponding to determining that the sound made by the human for the selected grapheme is incorrect.

A method for teaching grapheme-phoneme correspondence comprising:

• causing a display of a device to output a grapheme graphical user interface (GUI) that includes a grapheme for pronunciation by a human to teach the human a grapheme-phoneme correspondence;
• receiving audio data representative of a sound made by the human based on the grapheme displayed on the display;
• providing the audio data to a trained neural network model to determine whether the sound made by the human corresponds to a phoneme for the grapheme;
• and
• causing a speaker of the device to output a sound representative of the phoneme for the grapheme in response to determining that the sound made by the human does not correspond to the phoneme for the grapheme.

A computer-implemented system comprising:

• a tool configured to output a user-interface display view that shows a user a series of graphemes, prompts the user to say the sound each grapheme makes, and captures one or more spoken responses from the user in an audio file;
• a trained neural network model configured to recognize individual sounds spoken out loud in isolation;
• wherein the tool outputs the audio file to the trained neural network model to evaluate whether a response was correct or mistaken;
• and
• wherein the tool includes a feedback mechanism which is configured to provide modeling and repetition to the user when a mistaken response is detected.