Related papers: Massive Open-Vocabulary Keyword Spotting

Massive Open-Vocabulary Keyword Spotting

URL: http://arxiv.org/abs/2606.11279v1
Date: Tue, 09 Jun 2026 12:11:11 GMT
Title: Massive Open-Vocabulary Keyword Spotting
Abstract summary: We propose a system that stores features with a memory footprint up to 128 times smaller than a comparable baseline.<n>Our system achieves a comparable entity recall as uncompressed solutions, even in languages not seen during training.
Score: 2.8582274879786684
License: http://creativecommons.org/licenses/by/4.0/
Abstract: Automatic speech recognition systems have been shown to under-perform when it comes to transcribing words rarely seen in the training data, namely specialized terminology. Open-vocabulary keyword spotting, combined with contextual biasing, has been shown to mitigate this issue. However, existing systems can only handle glossaries of a few hundred terms without becoming an infeasible bottleneck. We propose a system that stores features with a memory footprint up to 128 times smaller than a comparable baseline and allows users to process massive databases while remaining open-vocabulary. Without fine-tuning the speech recognition model, our system achieves a comparable entity recall as uncompressed solutions, even in languages not seen during training.

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