Speech Processing and Understanding
Projects
TAPAS: Training Network on Automatic Processing of PAthological Speech
There are an increasing number of people across Europe with debilitating
speech pathologies (e.g., due to stroke, Parkinson's, etc). These
groups face communication problems that can lead to social exclusion.
They are now being further marginalised by a new wave of speech
technology that is increasingly woven into everyday life but which is
not robust to atypical speech. TAPAS is a Horizon 2020 Marie
Skłodowska-Curie Actions Innovative Training Network European Training
Network (MSCA-ITN-ETN) project that aims to transform the well being of
these people.
TAPAS adopts an inter-disciplinary and
multi-sectorial approach. The consortium includes clinical
practitioners, academic researchers and industrial partners, with
expertise spanning speech engineering, linguistics and clinical science.
All members have expertise in some element of pathological speech. This
rich network will train a new generation of 15 researchers, equipping
them with the skills and resources necessary for lasting success.
DysarTrain: Development of a digital therapy tool as an exercise supplement for speech disorders and facial paralysis
Dysarthrien sind neurologisch bedingte, erworbene Störungen des Sprechens. Dabei sind vor allem die Koordination und Ausführung der Sprechbewegungen, aber auch die Mimik betroffen. Besonders häufig tritt eine Dysarthrie nach einem Schlaganfall, Schädel-Hirn-Trauma oder bei neurologischen Erkrankungen wie Parkinson auf.
Ähnlich wie in allen Sprechtherapien erfordert auch die Behandlung der Dysarthrie ein intensives Training. Anhaltende Effekte der Dysarthrie-Therapie stellen sich deshalb nur …
Modelling the progression of neurological diseases
Develop speech technology that can allow unobtrusive monitoring of many kinds of neurological diseases. The state of a patient can degrade slowly between medical check-ups. We want to track the state of a patient unobtrusively without the feeling of constant supervision. At the same time the privacy of the patient has to be respected. We will concentrate on PD and thus on acoustic cues of changes. The algorithms should run on a smartphone, track acoustic changes during regular phone conversations…
DeepAL: Deep Learning Applied to Animal Linguistics
Deep Learning applied to animal linguistics in particular the analysis of underwater audio recordings of marine animals (killer whales):
The project includes the automatic segmentation of killer whale signals in noise-heavy and large underwater bioacoustic archives as well as a subsequent call type identification/classification in order to derive linguistic elements/patterns. In combination with the recorded situational video footage those patterns should help to decode the killer whale language.
Deep Learning based Noise Reduction for Hearing Aids
Reduction of unwanted environmental noises is an important feature of today’s hearing aids, which is why noise reduction is nowadays included in almost every commercially available device. The majority of these algorithms, however, is restricted to the reduction of stationary noises. Due to the large number of different background noises in daily situations, it is hard to heuristically cover the complete solution space of noise reduction schemes. Deep learning-based algorithms pose a possible so…
Participating Scientists
Prof. Dr.-Ing. Elmar Nöth
- Phone number: +49 9131 85-27888
- Email: elmar.noeth@fau.de
- Website: https://lme.tf.fau.de/person/noeth/
Philipp Klumpp, M. Sc.
- Phone number: +4991318527137
- Email: philipp.klumpp@fau.de
Colloquium time table
Publications
Speaker model to monitor the neurological state and the dysarthria level of patients with parkinson’s disease
Springer Verlag, 2017
ISBN: 9783319642055
DOI: 10.1007/978-3-319-64206-2_31
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Natural Language Analysis to Detect Parkinson’s Disease
22nd International Conference on Text, Speech, and Dialogue, TSD 2019 (Ljubljana, September 11, 2019 - September 13, 2019)
In: Kamil Ekštein (ed.): Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2019
DOI: 10.1007/978-3-030-27947-9_7
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Feature space visualization with spatial similarity maps for pathological speech data
20th Annual Conference of the International Speech Communication Association: Crossroads of Speech and Language, INTERSPEECH 2019 (Graz, September 15, 2019 - September 19, 2019)
In: Gernot Kubin, Thomas Hain, Bjorn Schuller, Dina El Zarka, Petra Hodl (ed.): Proc. Interspeech 2019 2019
DOI: 10.21437/Interspeech.2019-2080
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Towards an automatic evaluation of the dysarthria level of patients with Parkinson's disease
In: Journal of Communication Disorders 76 (2018), p. 21-36
ISSN: 0021-9924
DOI: 10.1016/j.jcomdis.2018.08.002
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2018/Vasquez-Correa18-TAA.pdf
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Unobtrusive Monitoring of Speech Impairments of Parkinson'S Disease Patients Through Mobile Devices
43rd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
DOI: 10.1109/ICASSP.2018.8462332
URL: https://ieeexplore.ieee.org/abstract/document/8462332
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Next Events:
Contact
Paula Andrea Pérez-Toro, M. Sc.
91058 Erlangen
- Phone number: +49 9131 85-27137
- Email: paula.andrea.perez@fau.de
- Website: https://lme.tf.fau.de/person/perez