Semantic Codebook Transformations for Mismatched Language Interpreters
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Solution Overview
Problem
Semantic communication between a transmitter and a receiver can be unsatisfactory due to mismatches between language generators and interpreters, leading to incorrect decoding of symbols and impaired transmission of semantic meaning, especially when the language generators and interpreters do not perfectly match, and when a receiver is not configured to receive semantic meaning from a different transmitter.
Innovation Solution
A method is proposed to semantically align symbols by applying transformations to create a codebook of transformations that can correctly decode symbols from one language generator to another, even when they do not perfectly match, by identifying transformations that maximize the transfer rate of information and including them in the codebook, which can be pruned to reduce complexity and improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If language generators and interpreters are used for semantic communication, then semantic meaning can be transmitted, but mismatches between them cause incorrect decoding and impaired transmission
Solution Approach 1:
The patent introduces a codebook as an intermediary component that mediates between the language generator and language interpreter. The codebook contains transformations that map symbols from one language generator's vocabulary to another's, enabling compatible communication even when the language generators and interpreters do not perfectly match. This intermediary resolves the contradiction by providing a translation layer that ensures reliable semantic transmission across different linguistic systems.
Solution Approach 2:
The patent applies parameter changes by transforming symbols through various mathematical transformations (such as linear transformations, nonlinear transformations, or embeddings) to adapt them between different language spaces. By changing the parameters or representation of symbols through these transformations, the system achieves compatibility between mismatched language generators and interpreters while maintaining semantic meaning.
2Measurement precision
If a codebook of transformations is constructed to align symbols between language generators, then communication accuracy improves, but computational complexity increases
Solution Approach 1:
The patent applies partial action by selecting and including only the most relevant transformations in the codebook rather than exhaustively including all possible transformations. This selective approach maintains sufficient decoding accuracy while reducing the computational complexity and size of the codebook, resolving the contradiction between precision and complexity.
Solution Approach 2:
The patent extracts and retains only the essential transformations needed for effective communication from the full set of possible transformations. By taking out and keeping only the most useful transformations in the codebook, the system achieves good symbol decoding accuracy with reduced computational overhead, balancing precision and complexity.
3Reliability
If transformations are applied to semantically align symbols, then semantic channel equalization is achieved, but processing time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing the transformations in a codebook before actual communication occurs. This allows the transformations to be readily available during transmission without requiring complex real-time computation, thus achieving semantic channel equalization while minimizing processing time delays.
Solution Approach 2:
The patent uses copying by storing pre-computed transformation mappings in the codebook that can be quickly referenced and applied during communication. Instead of performing complex transformations in real-time, the system copies and applies pre-established transformation rules, reducing processing time while maintaining communication reliability.
Data Source
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AI summary
A method for constructing a codebook of transformations to equalize a semantic channel between a language generator (λ) and a language interpreter (I), the language generator (λ) encoding base observations (bm) into base symbols (x) while preserving base semantic meanings (bs); the language interpreter (I) outputting target observations (tm) based on target symbols while preserving target semantic meanings (ts); the codebook comprising transformation(s) (T) transforming base symbols (xi) endowed with base semantic meanings (bsi) into target symbols (yj) endowed with target semantic meanings (tsj); the method comprises A10) identifying a transformation (T) for which a function of transfer rates ( ρPi→QjT) for an association (aij) between a base semantic meaning (bsi) and an inferred target semantic meaning (tsi) reaches at least a predetermined threshold; such transfer rate ( ρPi→QjT) representing a probability for base symbols (xi) endowed with a base semantic meaning (bsi) to be transformed by the transformation into inferred target symbols (yj) endowed with the inferred target semantic meaning (tsj).