Patentlyze first noticed the patent which was published on July 2 after Meta filed it back in December of 2025. The filing described an “apparatus” that surveilled a user and their surroundings constantly to craft a better workout. “The audible communications may be associated with contextual factors such as time of day, location, user activity, or digital interaction,” the patent said. “The audible communications may be transcribed, and an emotional-state machine learning model may interpret verbal and nonverbal cues to determine emotional indicators.”

According to the filing, Meta needs to know when a user laughs or sighs, where they are physically, and what objects they’re surrounded by. It would even like to know when you’ve taken your meds. “The AI assistant may listen to a user(s) at predefined times to hear various types of communication, such as sighs, laughter, and/or the tone(s) of a voice(s),” the patent said. “The AI assistant may use these inputs to quantify the user's emotional state or generate other insights about the user [...] in another example, the AI assistant may take multiple inputs in in addition to audio inputs (e.g., of a user's voice) to provide a summary of emotional trends based on various inputs (e.g., a happier emotional state associated with a particular time of day or at a time when medication is taken, etc.).”

The more data it has, the patent explains, the better it could understand a user’s moods. “The system increases the precision and reliability of emotional inference by aligning multimodal sensor inputs on synchronized timelines, which creates a novel data structure that supports richer emotional analysis,” it said. “These combined features deliver a technical improvement in automated audio interpretation, enabling continuous emotional monitoring on everyday devices.”

The emotional-analyzing AI would need far more than just a user’s words to determine moods over time. A longer description of the hypothetical training data for the AI included “attributes of thousands of objects” such as a user’s books, personal messages, and newspapers. “In some examples, audible communications may include speech (e.g., voice data), sighs, laughter, or other nonverbal sounds associated with an expression(s), an emotion(s), or ideas. In some examples, the audible communications may include the tone(s) of a voice of a user while making the communication(s),” it said.

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