Adding cross-utterance audio context to Conformer-Transducer ASR reduces WER/CER by 0.5 to 1.1 absolute points on four benchmarks, and a splicing-based batch scheme cuts training time by up to about 19%.
XLS-R: Self-supervised Cross-lingual Speech Repre- sentation Learning at Scale,
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Exploring Cross-Utterance Speech Contexts for Conformer-Transducer Speech Recognition Systems
Adding cross-utterance audio context to Conformer-Transducer ASR reduces WER/CER by 0.5 to 1.1 absolute points on four benchmarks, and a splicing-based batch scheme cuts training time by up to about 19%.