Personal Attribute Identification Cues for Prosopagnosia
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Solution Overview
Problem
Individuals with physical, neurological, and cognitive challenges, such as vision deficits or prosopagnosia, struggle to accurately identify individuals they are interacting with, limiting effective communication.
Innovation Solution
A system and method using personal attribute data, such as audio and image data, to capture and process unique characteristics of individuals, enabling identification through facial and speaker recognition, and providing visual or auditory cues to assist in recognizing unrecognizable individuals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If individuals with vision deficits or prosopagnosia rely on their auditory and visual faculties to identify individuals, then they can maintain natural interaction, but they are unable to accurately recognize unrecognizable individuals
Solution Approach 1:
The patent introduces a computing device as an intermediary that captures personal attribute data (audio and image), extracts reference vectors, and presents identification cues to the user. This mediator bridges the gap between the user's inability to recognize individuals and the need for accurate identification, allowing users with prosopagnosia or vision deficits to interact effectively while maintaining natural conversation flow.
2Measurement precision
If the system captures and processes personal attribute data to enable identification, then identification accuracy improves, but system complexity increases
Solution Approach 1:
The patent extracts only the essential personal attribute data (audio and image characteristics) needed for identification, converting complex sensory information into simplified reference vectors. This extraction process captures the critical identifying features while discarding unnecessary details, achieving high identification precision without requiring the full complexity of the original sensory data.
3Loss of time
If the system processes personal attribute data in real-time during interactions, then identification is provided timely, but computational resources are consumed
Solution Approach 1:
The system performs preliminary actions by capturing and processing personal attribute data during the interaction itself, rather than requiring separate identification steps. The computing device continuously monitors audio and image data, extracting reference vectors in real-time, so that identification is already prepared when needed, minimizing delays without requiring intensive post-interaction processing.
Data Source
AI summary
A method includes processing, using a speech recognizer, a first portion of audio data to generate a first lattice, and generating a first partial transcription for an utterance based on the first lattice. The method includes processing, using the recognizer, a second portion of the data to generate, based on the first lattice, a second lattice representing a plurality of partial speech recognition hypotheses for the utterance and a plurality of corresponding speech recognition scores. For each particular partial speech recognition hypothesis, the method includes generating a corresponding re-ranked score based on the corresponding speech recognition score and whether the particular partial speech recognition hypothesis shares a prefix with the first partial transcription. The method includes generating a second partial transcription for the utterance by selecting the partial speech recognition hypothesis of the second plurality of partial speech recognition hypotheses having the highest corresponding re-ranked score.