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Multilingual and Unsupervised Subword Modeling for Zero-Resource Languages

Publications associées (65)

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Transformer models such as GPT generate human-like language and are predictive of human brain responses to language. Here, using functional-MRI-measured brain responses to 1,000 diverse sentences, we first show that a GPT-based encoding model can predict t ...

Berlin2024

Training a Filter-Based Model of the Cochlea in the Context of Pre-Trained Acoustic Models

Philip Neil Garner

Auditory research aims in general to lead to understanding of physiological processes. By contrast, the state of the art in automatic speech processing (notably recognition) is dominated by large pre-trained models that are meant to be used as black-boxes. ...

2024

Sparse Autoencoders for Speech Modeling and Recognition

Selen Hande Kabil

Speech recognition-based applications upon the advancements in artificial intelligence play an essential role to transform most aspects of modern life. However, speech recognition in real-life conditions (e.g., in the presence of overlapping speech, varyin ...

EPFL2023

Many pathologies cause impairments in the speech production mechanism resulting in reduced speech intelligibility and communicative ability. To assist the clinical diagnosis, treatment and management of speech disorders, automatic pathological speech asses ...

EPFL2022

Matchertext: Towards Verbatim Interlanguage Embedding

Bryan Alexander Ford

Embedding text in one language within text of another is commonplace for numerous purposes, but usually requires tedious and error-prone “escaping” transformations on the embedded string. We propose a simple cross-language syntactic discipline, matchertext ...

2022

Kinesthetic motor-imagery training improves performance on lexical-semantic access

Sylvain Jean-François Harquel, Camille Bonnet

The objective of this study was to evaluate the effect of Motor Imagery (MI) training on language comprehension. In line with literature suggesting an intimate relationship between the language and the motor system, we proposed that a MI-training could imp ...

PUBLIC LIBRARY SCIENCE2022

Word-level Embeddings for Cross-Task Transfer Learning in Speech Processing

Milos Cernak, Pierre Anton Beckmann

Recent breakthroughs in deep learning often rely on representation learning and knowledge transfer. In recent years, unsupervised and self-supervised techniques for learning speech representation were developed to foster automatic speech recognition. Up to ...

EUROPEAN ASSOC SIGNAL SPEECH & IMAGE PROCESSING-EURASIP2021

PARSINLU: A Suite of Language Understanding Challenges for Persian

Despite the progress made in recent years in addressing natural language understanding (NLU) challenges, the majority of this progress remains to be concentrated on resource-rich languages like English. This work focuses on Persian language, one of the wid ...

2021

Explainable Phonology-based Approach for Sign Language Recognition and Assessment

Sandrine Tornay

Sign language technology, unlike spoken language technology, is an emerging area of research. Sign language technologies can help in bridging the gap between the Deaf community and the hearing community. One such computer-aided technology is sign language ...

EPFL2021

What is Trending on Wikipedia? Capturing Trends and Language Biases Across Wikipedia Editions

Pierre Vandergheynst, Nicolas Aspert, Volodymyr Miz, Benjamin Ricaud, Joëlle Hanna

In this work, we propose an automatic evaluation and comparison of the browsing behavior of Wikipedia readers that can be applied to any language editions of Wikipedia. As an example, we focus on English, French, and Russian languages during the last four ...

ACM2020