Speech-VGG: A deep feature extractor for speech processing. - Pierre Beckmann; Mikolaj Kegler; Hugues Saltini; Milos Cernak (CoRR, 2019)

Deep Speech Inpainting of Time-Frequency Masks. - Mikolaj Kegler; Pierre Beckmann; Milos Cernak (INTERSPEECH, 2020)

Word-Level Embeddings for Cross-Task Transfer Learning in Speech Processing. - Pierre Beckmann; Mikolaj Kegler; Milos Cernak (EUSIPCO, 2021)

BYOL-S: Learning Self-supervised Speech Representations by Bootstrapping. - Gasser Elbanna; Neil Scheidwasser-Clow; Mikolaj Kegler; Pierre Beckmann; Karl El Hajal; Milos Cernak (HEAR@NeurIPS, 2021)

SERAB: A Multi-Lingual Benchmark for Speech Emotion Recognition. - Neil Scheidwasser-Clow; Mikolaj Kegler; Pierre Beckmann; Milos Cernak (ICASSP, 2022)

Hybrid Handcrafted and Learnable Audio Representation for Analysis of Speech Under Cognitive and Physical Load. - Gasser Elbanna; Alice Biryukov; Neil Scheidwasser-Clow; Lara Orlandic; Pablo Mainar; Mikolaj Kegler; Pierre Beckmann; Milos Cernak (INTERSPEECH, 2022)

Rejecting Cognitivism: Computational Phenomenology for Deep Learning. - Pierre Beckmann; Guillaume Köstner; Inês Hipólito (CoRR, 2023)

An Alternative to Cognitivism: Computational Phenomenology for Deep Learning. - Pierre Beckmann; Guillaume Köstner; Inês Hipólito (Minds Mach., 2023)

Mechanistic Indicators of Understanding in Large Language Models. - Pierre Beckmann; Matthieu Queloz (CoRR, 2025)