Dynamic Keyword Model Assignment for Voice Recognition
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Solution Overview
Problem
Conventional mobile devices have limited sound models and keywords, leading to inaccurate detection of new keywords due to insufficient sampling, restricting user functionality and convenience.
Innovation Solution
A method and apparatus for assigning a target keyword to a function in electronic devices, where a list of keywords is received via a communication network, and a keyword model is downloaded and used to detect the target keyword, enabling accurate activation of functions upon detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users generate sound models by training based on limited utterances, then new keywords can be detected, but detection accuracy is low due to insufficient sampling
Solution Approach 1:
The patent applies preliminary action by pre-training sound models using a large number of utterances collected in advance from multiple users. Instead of training with limited user utterances at the time of keyword addition, the system prepares comprehensive sound models beforehand, ensuring high detection accuracy when new keywords are introduced to the device.
2Measurement precision
If manufacturers equip devices with pre-configured sound models, then keyword detection is reliable, but the number of detectable keywords is limited
Solution Approach 1:
The patent implements dynamics by enabling the sound model to dynamically adapt and expand its keyword recognition capability. The system maintains a base sound model with pre-trained keywords and allows dynamic addition of new keywords through user input. The sound model evolves from a static, limited set to a dynamic, expandable vocabulary while preserving detection accuracy through the pre-training foundation.
Solution Approach 2:
The patent applies universality by creating a sound model that serves multiple functions: it recognizes both pre-configured keywords and user-defined keywords. The single sound model structure handles diverse keyword types and functions, making the system versatile without requiring separate models for different keyword categories.
3Measurement precision
If extensive sampling is used to train accurate sound models, then detection accuracy improves, but power consumption and training time increase
Solution Approach 1:
The patent resolves this contradiction by performing the extensive sampling and model training in advance, during device manufacturing or initial setup. The computationally intensive work of processing large numbers of utterances is completed beforehand, allowing the device to operate with a ready-to-use, accurate sound model without consuming excessive power during normal operation.
Data Source
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AI summary
A method, performed in an electronic device, for assigning a target keyword to a function is disclosed. In this method, a list of a plurality of target keywords is received at the electronic device via a communication network, and a particular target keyword is selected from the list of target keywords. Further, the method may include receiving a keyword model for the particular target keyword via the communication network. In this method, the particular target keyword is assigned to a function of the electronic device such that the function is performed in response to detecting the particular target keyword based on the keyword model in an input sound received at the electronic device.