Speech Translation Using Dynamic Units and Latency Fillers
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Solution Overview
Problem
Conventional speech translation approaches face a trade-off between low latency and high accuracy, particularly when translating between significantly different languages, leading to awkward pauses due to varying grammatical structures and sentence orderings.
Innovation Solution
A dynamic translation unit (TU) model adjusts TU size based on language differences, using filler content to offset latency, ensuring accurate and continuous translation by generating filler words or sounds like 'uh' or 'um' to bridge gaps between translated units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the translation system waits for complete translation units to maintain accuracy, then translation accuracy is improved, but latency increases causing awkward pauses
Solution Approach 1:
The system performs preliminary translation of available speech segments and prepares translated units in advance. When a translation unit becomes available, it is immediately output with filler content to bridge gaps, rather than waiting for complete sentence-level translation. This preliminary action maintains accuracy by translating complete semantic units while reducing latency by outputting them as soon as they are ready.
Solution Approach 2:
Filler content acts as an intermediary element between translated units. The filler content (e.g., 'uh', 'um', or language-specific equivalents) bridges the temporal gaps between translated units, masking the latency without compromising translation accuracy. This intermediary allows the system to maintain high accuracy while creating a more natural, continuous audio output.
2Ease of manufacture
If the translation system uses fixed-size translation units, then processing is simplified, but translation accuracy deteriorates when translating between markedly different languages
Solution Approach 1:
The system dynamically adjusts translation unit sizes based on the specific language pair being translated. For markedly different languages, the system uses larger translation units to capture complete grammatical structures and semantic meanings. For similar languages, smaller units may be used. This dynamic adaptation maintains translation accuracy while keeping processing manageable through automated unit segmentation.
Solution Approach 2:
The system changes the parameter of translation unit size based on language similarity metrics. When detecting translation between markedly different languages, the system increases the average size of translation units to ensure complete grammatical structures are translated together, improving accuracy without requiring manual intervention.
3Loss of time
If the translation system reduces translation unit size to reduce latency, then latency is improved, but translation accuracy deteriorates
Solution Approach 1:
The system segments speech into translation units of optimized size that balance latency and accuracy. Rather than using uniformly small units that would reduce latency but hurt accuracy, or uniformly large units that would improve accuracy but increase latency, the system segments speech into units sized according to linguistic boundaries and translation complexity, achieving both low latency and high accuracy simultaneously.
Data Source
AI summary
A system translates audio content. Speech information is derived from the audio content in a source language. The system dynamically translates the speech information to a target language using a translatable unit (TU) model. The model determines a dynamic threshold that controls an amount of the speech information used to form TUs. Responsive to reaching a dynamic threshold for a TU, the model translates the TU to the target language to form a translated unit. Responsive to a delay between a most recent translated unit and a forthcoming translated unit exceeding a threshold time value, the system selects filler content that is in the target language to at least partially fill the delay. A translated audio signal is synthesized that is in the target language using the most recent translated unit and the filler content.