Papers with Google Cloud’s Speech-to-Text API
WER-BERT: Automatic WER Estimation with BERT in a Balanced Ordinal Classification Paradigm (2021.eacl-main)
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| Challenge: | Automatic Speech Recognition (ASR) systems are evaluated using Word Error Rate (WER) a higher WER means a lower percentage of errors between the ground truth and the transcription of the system. |
| Approach: | They propose a new balanced paradigm for automatic Word Error Rate estimation using a Librispeech dataset and a Google Cloud's Speech-to-Text API. |
| Outcome: | The proposed approach is more effective than regression in a classification setting, but suffers from heavy class imbalance. |