Audio-to-Text Entity Name Correction Using Source Lookup
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Solution Overview
Problem
Existing audio-to-text translation systems often inaccurately translate entity names due to their rarity in common speech, leading to incorrect translations and resource wastage in correction processes.
Innovation Solution
A system that utilizes named entity recognition and an identifier of the audio input's source to detect and correct entity names by performing a lookup in an entity name database, ensuring accurate translation and reducing resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard audio-to-text translation is used for entity names, then processing speed is maintained, but translation accuracy deteriorates due to rarity of entity names in common speech
Solution Approach 1:
The system performs preliminary processing by detecting potential entity names in the audio input before completing the full translation. Named entity recognition is applied to identify proper nouns, and these detected entities are preserved in their original form throughout the translation process, preventing mistranslation before it occurs.
Solution Approach 2:
The translation process is segmented into distinct stages: audio-to-text translation, named entity recognition on the translated text, and correction by replacing recognized entities with their original forms from the audio. This segmentation allows specialized handling of entity names separate from regular text translation.
2Measurement precision
If manual correction of mistranslated entity names is performed, then translation accuracy improves, but resource consumption increases
Solution Approach 1:
The system performs self-correction by automatically detecting mistranslated entity names through named entity recognition and replacing them with the correct original forms extracted from the audio input. This automated self-service eliminates the need for manual correction while maintaining high accuracy.
Solution Approach 2:
The system implements a feedback mechanism where the translated text is analyzed by named entity recognition, and the detected entities feed back into the translation output for correction. This closed-loop feedback automatically identifies and corrects mistranslations without additional manual intervention.
3Reliability
If entity names are preserved from audio input, then translation reliability improves, but system complexity increases due to additional processing steps
Solution Approach 1:
The system uses a multi-functional approach where the audio input serves multiple purposes: it is both translated into text and simultaneously used as a reference source for extracting original entity names. This universal use of the audio input reduces the need for separate entity databases or additional data sources.
Data Source
AI summary
In some implementations, a device may obtain an audio input. The device may perform an audio-to-text operation to translate the audio input into a first text output. The device may detect that a first portion of the first text output is to be modified to include an entity name. The device may perform, using an identifier of a source of the audio input, a lookup operation to identify the entity name. The device may modify the first text output to obtain a second text output by replacing the first portion with the entity name.