id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_jhgdjhqkh5dknobbgykk37oz4y	Prashanth Gurunath Shivakumar	Confusion2Vec: towards enriching vector space word representations with representational ambiguities	2019	49	.pdf	application/pdf	22298	4413	64	model word confusions efficiently, without compromising on the semantic-syntactic Keywords Confusion2vec, Word2vec, Embeddings, Word representations, Confusion networks, (2003) proposed feedforward neural network based language models which jointly learned the distributed word (i) linguistic context (modeled by word2vec like word vector representations), and word vectors are shown to encode efficient syntactic-semantic language information. Traditional word vector representations such as word2vec only model the contextual the bag-of-word model in a semantic-syntactic analogy task. for acoustic confusions parallel to the analogy task and the word similarity task. The shortcomings of the indomain model compared to the Google Word2Vec on the Semantic&Syntactic analogy task baseline models perform well on the word similarity tasks as expected. observation is that modeling the word confusions boost the semantic and syntactic scores of case of ASR, the word-confusion subspace is associated with the acoustic similarity of acoustic-confusion through word vector representations, the confusion2vec can provide	./cache/work_jhgdjhqkh5dknobbgykk37oz4y.pdf	./txt/work_jhgdjhqkh5dknobbgykk37oz4y.txt