Foreign Language Audio Search via Key Phrase Variant Generation
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Solution Overview
Problem
Conventional systems face challenges in accurately searching for a key phrase in a native language within an audio recording of a foreign language, as they may miss synonyms and struggle with out-of-vocabulary words, limiting recall and usability, especially when the user does not speak the foreign language.
Innovation Solution
A system that converts a key phrase from a first language into a second language, generates variants, and uses machine translation and pronunciation to create a searchable lattice in the foreign language, allowing for the identification of instances of the key phrase or its variants within the audio recording, even when the system lacks direct translations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional translation techniques are used to search for key phrases in foreign language audio, then the system can translate words between languages, but it misses synonyms and out-of-vocabulary words, reducing search accuracy
Solution Approach 1:
The system segments the search query into individual words and processes each word separately through translation and variation generation. This allows the system to handle each word independently, generating multiple variants for each word to capture synonyms and out-of-vocabulary words, thereby improving search accuracy without requiring perfect translation of the entire phrase.
Solution Approach 2:
Instead of requiring exact translation of every word, the system generates multiple variants for each translated word, including synonyms and related terms. This excessive action of generating multiple possibilities for each word compensates for translation inaccuracies and captures synonyms, improving overall search accuracy even when individual word translations are not perfect.
2Productivity
If the system uses a limited translation dictionary, then the system is simpler to implement, but it cannot accurately translate out-of-vocabulary words, reducing search performance
Solution Approach 1:
The system uses machine translation capabilities to automatically translate out-of-vocabulary words without requiring manual expansion of the translation dictionary. This self-service approach allows the system to handle words not in the predefined dictionary by leveraging external machine translation resources, improving search performance while avoiding the complexity of maintaining a comprehensive custom dictionary.
Solution Approach 2:
The system introduces machine translation as an intermediary layer between the limited translation dictionary and the search query. This intermediary allows the system to bridge the gap between predefined translations and out-of-vocabulary words, enabling accurate translation of words not in the dictionary while maintaining the simplicity of the original dictionary-based architecture.
3Reliability
If the system searches using only exact word matches in the foreign language, then the search is faster and simpler, but it cannot find synonyms or variations of the key phrase, reducing recall
Solution Approach 1:
The system performs preliminary action by generating multiple word variants and synonyms for each translated word before actually searching the audio transcript. This pre-computation of variations allows the search to capture synonyms and variations without requiring complex real-time processing during the search itself, improving recall while minimizing time loss.
Solution Approach 2:
The system changes the search parameters by transforming the original query into multiple variant forms with different wordings. Instead of searching for a single exact phrase, the system searches for multiple variants generated from the translated words, capturing synonyms and variations. This parameter transformation improves recall without significantly increasing search time as the variants are pre-generated.
Data Source
AI summary
Techniques are disclosed for searching audio recordings in a second language with a key phrase in a first language. For example, a system as described herein receives a first key phrase in the first language and an audio recording in the second language. The system converts the first key phrase into a second key phrase in the second language. The system processes the second key phrase to produce a second key phrase variant. The system identifies, from a graph of words in the second language generated from the audio recording, instances of the second key phrase or the second key phrase variant within the audio recording. The system displays the identified instances of the second key phrase or the second key phrase variant within the audio recording to enhance searchability of the audio recording in the second language.