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Found 4 papers, 3 papers with code
Accented Speech Recognition With Accent-specific Codebooks
In this work, we propose a novel accent adaptation approach for end-to-end ASR systems using cross-attention with a trainable set of codebooks.
Adaptive Discounting of Implicit Language Models in RNN-Transducers
RNN-Transducer (RNN-T) models have become synonymous with streaming end-to-end ASR systems.
Multilingual and code-switching ASR challenges for low resource Indian languages
For this purpose, we provide a total of ~600 hours of transcribed speech data, comprising train and test sets, in these languages including two code-switched language pairs, Hindi-English and Bengali-English.
Coupled Training of Sequence-to-Sequence Models for Accented Speech Recognition
We propose coupled training for encoder-decoder ASR models that acts on pairs of utterances corresponding to the same text spoken by speakers with different accents.
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