Speech Recognition False Correction via Content-Based Method Selection
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Solution Overview
Problem
Conventional speech recognition technologies struggle to accurately recognize user speech due to false recognition issues, especially when predicting the content of the speech before recognition, leading to ineffective device control.
Innovation Solution
A method that determines the content of user speech based on text data from recognition results, selects a suitable correction method from multiple options, and applies it to correct false recognition, without requiring prior information about the speech content, using techniques like converting words into similar phonemes, parameters, or context-dependent corrections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional speech recognition technology is used to convert speech to character strings, then the basic speech-to-text function is achieved, but false recognition occurs leading to inaccurate device control
Solution Approach 1:
The system determines the content of the speech based on the recognition result, selects an appropriate correction method based on this determined content, and corrects false recognition accordingly. This feedback loop enables the system to adaptively improve recognition accuracy by analyzing the context and applying targeted corrections.
Solution Approach 2:
The system performs preliminary determination of speech content and selection of correction methods before finalizing the recognition result. By anticipating potential false recognition issues and preparing correction strategies in advance, the system can more effectively resolve ambiguities and improve overall recognition accuracy.
2Adaptability or versatility
If multiple correction methods are available for false recognition, then correction flexibility is improved, but system complexity increases
Solution Approach 1:
The system dynamically selects from multiple correction methods based on the determined content of the speech. Rather than applying a fixed correction approach, the system adapts its correction strategy in real-time according to the specific context and type of false recognition detected, optimizing correction effectiveness while managing complexity through conditional logic.
Data Source
AI summary
A method includes determining a content of a speech of a user on the basis of text data including a word string acquired as a recognition result of the speech, selecting a correction method suitable for the determined content of the speech from among multiple correction methods for correcting false recognition contained in the text data, and correcting the false recognition contained in the text data using the selected correction method.