Translation Compression via Symbolic Encoding
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Solution Overview
Problem
Current machine translation systems face challenges in efficiently translating text across multiple languages due to high memory and computational requirements, especially in multilingual platforms, where storing multiple translations is impractical and on-demand translation can be computationally expensive, and searching for content in different languages is difficult.
Innovation Solution
Implementing compression techniques such as byte-pair encoding and beam search branch storage to represent translations in memory, allowing for efficient retrieval and decoding of translations, and enabling search functionality across encoded text representations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple translations are stored for each text in multilingual platforms, then translation quality and availability are improved, but memory requirements and storage costs increase significantly
Solution Approach 1:
The patent creates compressed symbolic copies of translations instead of storing full text representations. Each translation is encoded into a compact symbolic form that preserves the essential meaning while occupying minimal storage space, allowing multiple translations to be stored without proportionally increasing memory requirements
Solution Approach 2:
The patent transforms translations from their original text form into a different parameter representation (symbolic encoding). This parameter change compresses the data structure from verbose natural language into compact symbolic sequences, dramatically reducing storage requirements while maintaining translation quality
2Quantity of substance
If on-demand translation is implemented to reduce storage costs, then memory requirements are reduced, but computational expense and translation time increase
Solution Approach 1:
The patent performs preliminary encoding of translations into symbolic form during the translation process itself. This preliminary action prepares the data in a compressed state before storage, so that when translations are retrieved, they can be quickly decoded without requiring expensive real-time translation computations
Solution Approach 2:
The patent introduces symbolic encodings as an intermediary representation between the original text and the target language translation. This intermediary form allows for efficient storage and rapid retrieval, acting as a bridge that reduces both storage requirements and computational overhead for on-demand translation
3Quantity of substance
If compressed representations are stored instead of full translations, then storage efficiency is improved, but retrieval and decoding complexity increases
Solution Approach 1:
The patent segments translations into discrete symbolic units that can be independently stored and retrieved. This segmentation allows the compression system to break down complex translations into manageable symbolic components, making the retrieval and decoding process more systematic and less complex
Data Source
AI summary
Devices and techniques are generally described for translation compression. In various examples, first text comprising at least one word composed in a first language may be determined. In some examples, first data that indicates a target language for translation may be received. First symbol data representing an encoded translation of the first text in the target language may be retrieved from memory. A symbol decoder may be determined for decoding the first symbol data. Second text may be generated by inputting the first symbol data into the symbol decoder. The second text may represent a translation of the first text into the target language. In various examples, the second text may be output as video and/or audio.