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Found 4 papers, 1 papers with code
Worse WER, but Better BLEU? Leveraging Word Embedding as Intermediate in Multitask End-to-End Speech Translation
Speech translation (ST) aims to learn transformations from speech in the source language to the text in the target language.
Training a code-switching language model with monolingual data
A lack of code-switching data complicates the training of code-switching (CS) language models.
Sequence-to-sequence Automatic Speech Recognition with Word Embedding Regularization and Fused Decoding
This allows the decoder to consider the semantic consistency during decoding by absorbing the information carried by the transformed decoder feature, which is learned to be close to the target word embedding.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Personalized word representations Carrying Personalized Semantics Learned from Social Network Posts
In this framework, universal background word vectors are first learned from the background corpora, and then adapted by the personalized corpus for each individual user to learn the personalized word vectors.
