Machine Translation Apparatus Automatic Question Answering
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Solution Overview
Problem
Current speech translation systems face challenges in reducing user burdens during multilingual dialogues, as they require manual responses and lack the ability to automatically answer questions, leading to increased cognitive load and inefficiency.
Innovation Solution
A machine translation apparatus comprising a machine translation unit, a retrieval unit, and a determination unit that performs speech recognition, retrieves similar question sentences, and determines whether to provide pre-stored answer sentences or translate questions based on similarity thresholds, allowing for automatic question answering and reduced dialog burdens.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If the system uses traditional machine translation for all user inputs, then translation coverage is maintained, but user burden increases due to lack of automatic responses
Solution Approach 1:
The system pre-stores question sentences and answer sentences in the storage unit before runtime. During operation, the retrieval unit quickly matches incoming speech against these pre-prepared questions, enabling automatic responses without real-time translation delays. This preliminary preparation reduces user burden by providing instant automatic answers for common questions.
Solution Approach 2:
The system enables self-service through automatic question answering. When the determination unit identifies that an incoming speech matches a stored question sentence, the system automatically selects and outputs the corresponding answer without requiring user intervention or manual translation. This self-service capability reduces user burden by handling routine inquiries autonomously.
2Productivity
If the system retrieves similar question sentences from storage, then automatic answering is enabled for common questions, but translation accuracy may decrease for unique questions
Solution Approach 1:
The system dynamically adjusts its response strategy based on the similarity degree calculated by the determination unit. When similarity exceeds the threshold, the system dynamically switches to automatic answer selection mode. When similarity is at or below the threshold, it dynamically switches to traditional machine translation mode. This dynamic adaptation maintains translation accuracy for unique questions while improving dialog efficiency for common questions.
Solution Approach 2:
The system uses a similarity threshold parameter to control the switching between automatic answering and machine translation modes. By comparing the calculated similarity degree against this parameter, the determination unit decides whether to retrieve pre-stored answers or perform full machine translation. This parameter-based control optimizes both dialog efficiency and translation accuracy based on the specific input characteristics.
3Speed
If the system stores pre-prepared question and answer sentences, then automatic responses are faster, but system complexity increases
Solution Approach 1:
The system segments the speech processing function into distinct modules: the retrieval unit for matching questions, the determination unit for similarity assessment, and the machine translation unit for translating unmatched speech. This segmentation allows the system to achieve fast automatic responses for common questions while maintaining a clear, manageable system structure where each component has a specific responsibility.
Solution Approach 2:
The storage unit serves multiple functions: it stores question sentences for retrieval, stores answer sentences for automatic responses, and indirectly supports the machine translation unit by providing reference data. This multi-functionality reduces overall system complexity by consolidating storage operations into a single unit rather than requiring separate storage systems for each function.
Data Source
AI summary
According to one embodiment, a machine translation apparatus includes the following elements. The machine translation unit performs machine translation on a first text in a first language to generate a first machine translation result in a second language. The retrieval unit retrieves a first question sentence in the first language similar to the first text to obtain a degree of similarity between the first text and the first question sentence. The determination unit determines a first answer sentence in the first language corresponding to the first question sentence to be an output target when the degree of similarity is higher than a threshold and determines the first machine translation result to be an output target when the degree of similarity is lower than the threshold.