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Aharon Satt

2 accepted papers

2023

Modeling Turn-Taking in Human-To-Human Spoken Dialogue Datasets Using Self-Supervised Features

ICASSP 2023accepted

Self-supervised pre-trained models have consistently delivered state-of-art results in the fields of natural language and speech processing. However, we argue that their merits for modeling Turn-Taking for spoken dialogue systems still need further investigation. Due to that, in this paper we intro-…

Cited by 0SourceScholar
2022

A New Data Augmentation Method for Intent Classification Enhancement and its Application on Spoken Conversation Datasets

ICASSP 2022accepted

Intent classifiers are vital to the successful operation of virtual agent systems. This is especially so in voice activated systems where the data can be noisy with many ambiguous directions for user intents. Before operation begins, these classifiers are generally lacking in real-world training dat…

Cited by 0SourceScholar