no code implementations • • Mickaël Rigault, Claudia Cevenini, Khalid Choukri, Martin Kocour, Karel Veselý, Igor Szoke, Petr Motlicek, Juan Pablo Zuluaga-Gomez, Alexander Blatt, Dietrich Klakow, Allan Tart, Pavel Kolčárek, Jan Černocký
In this paper the authors detail the various legal and ethical issues faced during the ATCO2 project.
1 code implementation • 8 Nov 2022 • Juan Zuluaga-Gomez, Karel Veselý, Igor Szöke, Petr Motlicek, Martin Kocour, Mickael Rigault, Khalid Choukri, Amrutha Prasad, Seyyed Saeed Sarfjoo, Iuliia Nigmatulina, Claudia Cevenini, Pavel Kolčárek, Allan Tart, Jan Černocký
In this paper, we introduce the ATCO2 corpus, a dataset that aims at fostering research on the challenging ATC field, which has lagged behind due to lack of annotated data.
One of the factors causing such degradation may be intrinsic speaker variability, such as emotions, occurring commonly in realistic speech.
The introduced data augmentation adds additional performance on high WER transcripts and allows the adaptation of the model to unseen airspaces.
We modify the acoustic model to predict joint state posteriors for all speakers, enabling the network to express uncertainty about the attribution of parts of the speech signal to the speakers.
We propose to express the forward-backward algorithm in terms of operations between sparse matrices in a specific semiring.
Results show that `unseen domains' (e. g. data from airports not present in the supervised training data) are further aided by contextual SSL when compared to standalone SSL.
The proposed English Language Detection (ELD) system is based on the embeddings from Bayesian subspace multinomial model.
This paper describes joint effort of BUT and Telef\'onica Research on development of Automatic Speech Recognition systems for Albayzin 2020 Challenge.