Speech Translation Vocabulary Update via User Customization
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Solution Overview
Problem
Existing speech-to-speech translation systems are limited by their pre-defined vocabularies, which fail to adapt to new words and language usage in field situations, requiring expert modifications and linguistic knowledge, making them impractical for real-world use.
Innovation Solution
A field-maintainable speech-to-speech translation system with a user-friendly customization module that allows users to add new words and phrases without technical expertise, using a multimodal interface for input and feedback, and updating vocabulary across all system components dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the system uses a pre-defined vocabulary determined by developers, then the system structure remains simple and stable, but the system cannot adapt to new words and language usage in field situations
Solution Approach 1:
The system enables users to add new words and expressions independently without requiring developer intervention or linguistic expertise. The user interface allows direct modification of the vocabulary database, and the system automatically integrates these additions across all processing modules, making the system self-updatable by end users.
Solution Approach 2:
The vocabulary database transitions from a static, pre-defined structure to a dynamic, user-modifiable structure. New words can be added at any time during field operations, and the system continuously adapts its recognition and translation capabilities based on user input, making the vocabulary flexible and evolving rather than fixed.
2Adaptability or versatility
If users can add new words to the system, then the system becomes adaptable to field needs, but modifying multiple components and retraining modules becomes extraordinarily difficult requiring expert knowledge
Solution Approach 1:
A user interface layer acts as an intermediary between the user and the complex system components. This interface abstracts away the complexity of modifying multiple modules and retraining models, presenting users with simple operations for adding words while handling all underlying technical processes automatically in the background.
Solution Approach 2:
The system separates the user-facing vocabulary management function from the underlying complex processing modules. Users interact with a simplified interface for adding words, while the system internally manages the segmentation and coordination of updates across speech recognition, translation, and synthesis modules without requiring users to understand or manually configure each component.
3Reliability
If the system retraines about 20 different modules to learn a new word, then the system maintains integrated functioning, but the process requires extensive time, expertise, and cost
Solution Approach 1:
The system performs preliminary organization of the vocabulary database and module update procedures during system development. When users add new words, pre-configured update mechanisms automatically propagate changes across all 20 modules without requiring on-the-spot retraining or expert intervention, reducing field modification time significantly.
Solution Approach 2:
The system implements automated feedback loops that monitor vocabulary additions and trigger appropriate updates across all processing modules. When a user adds a new word, the system automatically detects this change and coordinates updates through the speech recognition, translation, and synthesis pipelines, ensuring integrated functioning without manual intervention.
4Productivity
If out-of-vocabulary words are misrecognized as in-vocabulary words, then the system maintains operation with limited vocabulary, but communication accuracy breaks down
Solution Approach 1:
The system dynamically changes the vocabulary parameter by allowing user addition of new words during field operations. When users encounter out-of-vocabulary words, they can add these words directly to the system, immediately expanding the vocabulary database and preventing future misrecognitions, thus maintaining both operation continuity and accuracy.
Data Source
AI summary
A method and apparatus are provided for updating the vocabulary of a speech translation system for translating a first language into a second language including written and spoken words. The method includes adding a new word in the first language to a first recognition lexicon of the first language and associating a description with the new word, wherein the description contains pronunciation and word class information. The new word and description are then updated in a first machine translation module associated with the first language. The first machine translation module contains a first tagging module, a first translation model and a first language module, and is configured to translate the new word to a corresponding translated word in the second language. Optionally, the invention may be used for bidirectional or multi-directional translation.