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As a first step towards a complete computational model of speech learning involving perception-production loops, we investigate the forward mapping between pseudo-motor commands and articulatory trajectories. Two phonological feature sets, based resp
Externí odkaz:
http://arxiv.org/abs/2408.04363
Most speech self-supervised learning (SSL) models are trained with a pretext task which consists in predicting missing parts of the input signal, either future segments (causal prediction) or segments masked anywhere within the input (non-causal pred
Externí odkaz:
http://arxiv.org/abs/2405.20101
Publikováno v:
Interspeech, ISCA, Aug 2023, Dublin, Ireland
Hard of hearing or profoundly deaf people make use of cued speech (CS) as a communication tool to understand spoken language. By delivering cues that are relevant to the phonetic information, CS offers a way to enhance lipreading. In literature, ther
Externí odkaz:
http://arxiv.org/abs/2306.08290
Autor:
Arne Jordan, Julia Nothacker, Valentina Paucke, Klaus Heinz Hager, Susann Hueber, Arian Karimzadeh, Thomas Kötter, Christin Löffler, Beate Sigrid Müller, Daniel Tajdar, Dagmar Lühmann, Martin Scherer, Ingmar Schäfer
Publikováno v:
JMIR Public Health and Surveillance, Vol 10, p e58711 (2024)
BackgroundAs a result of climate change, exposure to high temperatures is becoming more common, even in countries with temperate climates. For patients with chronic diseases, heat poses significant health risks. Empowering patients is a crucial eleme
Externí odkaz:
https://doaj.org/article/48f21660b46749c0904ec5f56a51f0b2
Several recent studies have tested the use of transformer language model representations to infer prosodic features for text-to-speech synthesis (TTS). While these studies have explored prosody in general, in this work, we look specifically at the pr
Externí odkaz:
http://arxiv.org/abs/2207.01718
The human perception system is often assumed to recruit motor knowledge when processing auditory speech inputs. Using articulatory modeling and deep learning, this study examines how this articulatory information can be used for discovering speech un
Externí odkaz:
http://arxiv.org/abs/2206.08790
Autor:
Johannes Knitza, Koray Tascilar, Franziska Fuchs, Jacob Mohn, Sebastian Kuhn, Daniela Bohr, Felix Muehlensiepen, Christina Bergmann, Hannah Labinsky, Harriet Morf, Elizabeth Araujo, Matthias Englbrecht, Wolfgang Vorbrüggen, Cay-Benedict von der Decken, Stefan Kleinert, Andreas Ramming, Jörg H W Distler, Peter Bartz-Bazzanella, Nicolas Vuillerme, Georg Schett, Martin Welcker, Axel Hueber
Publikováno v:
Journal of Medical Internet Research, Vol 26, p e55542 (2024)
BackgroundThe diagnosis of inflammatory rheumatic diseases (IRDs) is often delayed due to unspecific symptoms and a shortage of rheumatologists. Digital diagnostic decision support systems (DDSSs) have the potential to expedite diagnosis and help pat
Externí odkaz:
https://doaj.org/article/2d37aa700fa44b96886fc7d0fb1095ed
Publikováno v:
BMJ Open, Vol 14, Iss 7 (2024)
Objectives Medical overuse exposes patients to unnecessary risks of harm. It is an open question whether and how patients perceive the concept of medical overuse, its causes and negative consequences.Design A qualitative study design, using elements
Externí odkaz:
https://doaj.org/article/1747e9d9718348318fe847ae803e28a2
Publikováno v:
ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing, May 2022, Singapour, Singapore
This paper proposes a simple and effective approach for automatic recognition of Cued Speech (CS), a visual communication tool that helps people with hearing impairment to understand spoken language with the help of hand gestures that can uniquely id
Externí odkaz:
http://arxiv.org/abs/2204.04965
We propose a computational model of speech production combining a pre-trained neural articulatory synthesizer able to reproduce complex speech stimuli from a limited set of interpretable articulatory parameters, a DNN-based internal forward model pre
Externí odkaz:
http://arxiv.org/abs/2204.02269