Wiki-En-ASR-Adapt: Large-scale synthetic dataset for English ASR Customization

• URL: http://arxiv.org/abs/2309.17267v1
• Date: Fri, 29 Sep 2023 14:18:59 GMT
• Title: Wiki-En-ASR-Adapt: Large-scale synthetic dataset for English ASR Customization
• Authors: Alexandra Antonova
• Abstract summary: We present a first large-scale public synthetic dataset for contextual spellchecking customization of automatic speech recognition (ASR) The proposed approach allows creating millions of realistic examples of corrupted ASR hypotheses and simulate non-trivial biasing lists for the customization task. We report experiments with training an open-source customization model on the proposed dataset and show that the injection of hard negative biasing phrases decreases WER and the number of false alarms.
• Score: 66.22007368434633
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present a first large-scale public synthetic dataset for contextual spellchecking customization of automatic speech recognition (ASR) with focus on diverse rare and out-of-vocabulary (OOV) phrases, such as proper names or terms. The proposed approach allows creating millions of realistic examples of corrupted ASR hypotheses and simulate non-trivial biasing lists for the customization task. Furthermore, we propose injecting two types of ``hard negatives" to the simulated biasing lists in training examples and describe our procedures to automatically mine them. We report experiments with training an open-source customization model on the proposed dataset and show that the injection of hard negative biasing phrases decreases WER and the number of false alarms.

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