Audio-Linguistic Embeddings for Spoken Sentences

Michelle Guo
Michelle Guo
Prateek Verma
Prateek Verma

ICASSP, 2019.

Cited by: 12|Bibtex|Views92
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

We propose spoken sentence embeddings which capture both acoustic and linguistic content. While existing works operate at the character, phoneme, or word level, our method learns long-term dependencies by modeling speech at the sentence level. Formulated as an audio-linguistic multitask learning problem, our encoder-decoder model simultan...More

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