In this paper we propose a novel virtual simulation-pilot engine for speeding up air traffic
controller (ATCo) training by integrating different state-of-the-art artificial intelligence (AI) …

Advances in Automatic Speech Recognition (ASR) over the last decade opened new areas
of speech-based automation such as in Air-Traffic Control (ATC) environment. Currently …

Speech signals contain a lot of sensitive information, such as the speaker's identity, which
raises privacy concerns when speech data get collected. Speaker anonymization aims to …

In this work, we investigate if the wav2vec 2.0 self-supervised pretraining helps mitigate the
overfitting issues with connectionist temporal classification (CTC) training to reduce its …

In this work, we propose lattice-free MMI (LFMMI) for supervised adaptation of self-
supervised pretrained acoustic model. We pretrain a Transformer model on thousand hours …

Transfer learning from large multilingual pretrained models, like XLSR, has become the new
paradigm for Automatic Speech Recognition (ASR). Considering their ever-increasing size …

The growing use of voice user interfaces has led to a surge in the collection and storage of
speech data. While data collection allows for the development of efficient tools powering …

Self-supervised models trained with high linguistic diversity, such as the XLS-R model, can
be effectively fine-tuned for the language recognition task. Typically, a back-end classifier …

In this paper, we perform an exhaustive evaluation of different representations to address
the intent classification problem in a Spoken Language Understanding (SLU) setup. We …

In this paper, we develop Automatic Speech Recognition (ASR) systems for multi-genre
speech recognition of low-resource languages where training data is predominantly …