Voice Recognition Module Dynamic Database Extension
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Solution Overview
Problem
Existing voice recognition electronic devices face challenges in accurately interpreting user queries due to variations in dialects and pronunciation, leading to failed recognition and inability to find matching answers in voice databases.
Innovation Solution
The electronic device employs a voice signal recognition module that converts user voice signals to text, searches both a base and an extension voice database, uses a best fit algorithm to find similar queries, outputs potential queries for user selection, and updates the database with new queries, ensuring accurate interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If voice recognition uses fixed database with predetermined questions, then system structure is simple, but recognition accuracy decreases due to dialect and pronunciation variations
Solution Approach 1:
The voice database transitions from a static fixed structure to a dynamic extendable structure. The system automatically extends the database by learning new voice patterns and questions from users, allowing the database to adapt and grow based on actual usage and user-specific characteristics rather than remaining rigid and predetermined.
Solution Approach 2:
The system performs self-learning and self-extension of the voice database without requiring manual programming of all possible questions and answers. The electronic device autonomously processes user voice inputs, identifies new patterns, and extends the database accordingly, enabling the system to serve itself in expanding its capabilities.
2Adaptability or versatility
If voice recognition relies on text conversion and database searching, then interaction is automated, but fails when voice patterns differ from recorded examples
Solution Approach 1:
The system incorporates feedback mechanisms where user responses and corrections are processed to refine future recognition. When the system encounters voice patterns that don't match existing database entries, it learns from these instances and adjusts its recognition models, creating a feedback loop that continuously improves adaptability to different dialects and pronunciation styles.
Data Source
AI summary
An interactive voice recognition electronic device converts a received voice signal to a text, and searches a voice databases to find a matched voice text of the converted text. The matched voice text is taken as a recognized voice text of the voice signal if the matched voice text exists in the voice database. The electronic device obtains a predetermined number of similar voice texts if no matched voice text exists in the voice database. The electronic device converts the predetermined number of similar voice texts to the voice signals, outputs the converted voice signals in turn, and selects one of the similar voice texts as the recognized voice text according to the selection of the user. The electronic device obtains the associated answer text of the recognized voice text in the voice database and converts the answer text to voice signals.