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Found 5 papers, 1 papers with code
Syn2Vec: Synset Colexification Graphs for Lexical Semantic Similarity
In this paper we focus on patterns of colexification (co-expressions of form-meaning mapping in the lexicon) as an aspect of lexical-semantic organization, and use them to build large scale synset graphs across BabelNet’s typologically diverse set of 499 world languages.
Mitigating the Exposure Bias in Sentence-Level Grapheme-to-Phoneme (G2P) Transduction
Text-to-Text Transfer Transformer (T5) has recently been considered for the Grapheme-to-Phoneme (G2P) transduction.
INTapt: Information-Theoretic Adversarial Prompt Tuning for Enhanced Non-Native Speech Recognition
INTapt is trained simultaneously in the following two manners: (1) adversarial training to reduce accent feature dependence between the original input and the prompt-concatenated input and (2) training to minimize CTC loss for improving ASR performance to a prompt-concatenated input.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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SPADE: Self-supervised Pretraining for Acoustic DisEntanglement
Self-supervised representation learning approaches have grown in popularity due to the ability to train models on large amounts of unlabeled data and have demonstrated success in diverse fields such as natural language processing, computer vision, and speech.
SMSMix: Sense-Maintained Sentence Mixup for Word Sense Disambiguation
To the best of our knowledge, this is the first attempt to apply mixup in NLP while preserving the meaning of a specific word.
