activity
20172021
most citedASR error management for improving spoken language understanding

3 citations · 3 across the 3 of their papers we have counts for

collaborators

6 papers

eess.AS2021

Overlap-aware low-latency online speaker diarization based on end-to-end local segmentation

Juan M. Coria, Hervé Bredin, Sahar Ghannay +1

We propose to address online speaker diarization as a combination of incremental clustering and local diarization applied to a rolling buffer updated every 500ms. Every single step…

cs.CL2020

LIMSI_UPV at SemEval-2020 Task 9: Recurrent Convolutional Neural Network for Code-mixed Sentiment Analysis

Somnath Banerjee, Sahar Ghannay, Sophie Rosset +2

This paper describes the participation of LIMSI UPV team in SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text. The proposed approach competed in SentiMix Hin…

cs.LG2020

A Comparison of Metric Learning Loss Functions for End-To-End Speaker Verification

Juan M. Coria, Hervé Bredin, Sahar Ghannay +1

Despite the growing popularity of metric learning approaches, very little work has attempted to perform a fair comparison of these techniques for speaker verification. We try to fi…

cs.CL2018

End-to-end named entity extraction from speech

Sahar Ghannay, Antoine Caubrière, Yannick Estève +2

Named entity recognition (NER) is among SLU tasks that usually extract semantic information from textual documents. Until now, NER from speech is made through a pipeline process th…

cs.CL2018

TED-LIUM 3: twice as much data and corpus repartition for experiments on speaker adaptation

François Hernandez, Vincent Nguyen, Sahar Ghannay +2

In this paper, we present TED-LIUM release 3 corpus dedicated to speech recognition in English, that multiplies by more than two the available data to train acoustic models in comp…

cs.CL20173 cited

ASR error management for improving spoken language understanding

Edwin Simonnet, Sahar Ghannay, Nathalie Camelin +2

This paper addresses the problem of automatic speech recognition (ASR) error detection and their use for improving spoken language understanding (SLU) systems. In this study, the S…