Papers with Conformer

2 papers
ChildMandarin: A Comprehensive Mandarin Speech Dataset for Young Children Aged 3-5 (2025.acl-long)

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Challenge: Automatic speech recognition systems have advanced significantly with models like Whisper, Conformer, and self-supervised frameworks such as Wav2vec 2.0.
Approach: They propose to use Mandarin speech datasets to analyze pronunciation and tone of children aged 3 to 5 and evaluate their models on speaker verification (SV) They find that the datasets are more robust than those used by adult speech recognition systems and are open-source and available for all academic purposes.
Outcome: The proposed dataset includes 41.25 hours of speech with carefully crafted manual transcriptions, collected from 397 speakers across various provinces in China, with balanced gender representation.
How Do Hyenas Deal with Human Speech? Speech Recognition and Translation with ConfHyena (2024.lrec-main)

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Challenge: Currently, attention-based models face computational hurdles in processing long sequences due to its quadratic complexity.
Approach: They propose a conformer whose encoder self-attentions are replaced with Hyena for speech processing . they propose 'confhyena' model that reduces training time by 27% at minimal cost .
Outcome: The proposed model reduces training time by 27% at the cost of minimal quality degradation.

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