Welcome back to Beyond the Patterns. Today I have the great pleasure to announce a new
colleague here at Friedrich Alexander University along Nürnberg and his name is Tobias Reichenbach.
So he leads a research group on sensory neuroengineering here at our university, did his masters in
physics at the University of Leipzig and his PhD also in physics at the Ludwig Maximilian
University in Munich. Previously he worked with the Kavli Prize winner Professor Hasbeth
at the Rockefeller University in New York and led a research group at Imperial College
London. His multi-disciplinary research combines methods from artificial intelligence with
computational neuroscience and neuroimaging to advance our understanding of the neuroprocessing
of complex natural signals with applications in medicine and technology. He has published
more than 50 peer-reviewed articles of which some have appeared in leading multi-disciplinary
journals such as Nature, Neuron and the Proceedings of the National Academy of Sciences. Dr.
Reichenbach is also a reviewing editor for eLive, a renowned journal in the life sciences.
Today we have the great pleasure to hear a presentation by him and it's entitled Decoding
the Neuroprocessing of Speech. Tobias, it's a great pleasure to have you here and the
stage is yours.
Thank you very much for the very kind introduction and of course also the invitation to speak
here also in this online form and in this recorded form. I think it's a great way to
reach a really good audience. So as I said, I work on sensory neuroengineering and just
wanted to broadly introduce the aims that we have there. So we typically think of our
brain as processing five different kinds of information if you want, us having five different
sensors, vision, touch, smell, hearing and taste. And the general aims that we have in
sensory neuroengineering is to on the one hand understand the neuro-voluntary of sensing,
then second to also aid people or to understand impairments that occur with the processing
of these different sensor information and third to also then of course rehabilitate
or help people to overcome some of the limitations that come with these impairments. Now a lot
of my work really focuses on speech and hearing and one of the main difficulties or as I said,
let's first go from the healthy person. So for us as healthy people that have normal
hearing we have an amazing ability to understand speech even in difficult listening environments.
So many everyday environments that we are in are often quite noisy. Think of car traffic
or if you're in a busy bar or restaurant and you have a lot of other background noise
around you. And despite that background noise as healthy individuals we're very well able
to nonetheless understand a particular target person and have a conversation with them.
And I would like to give you some audio demonstration to illustrate that this is really a non-trivial
problem. So I have several audio examples. I will ask you to listen to these and see
what you can understand of a particular target speech. So the first example that I want to
play you, you will hear a female voice amidst background noise. So there will be several
background speakers. Actually the audio recording will start without background noise. And then
after a few seconds that female voice will also start to say one sentence. That sentence
will start with a word footprints. So please listen for that word footprints and try to
hear if you can understand that sentence that that female person is saying.
So who heard the word footprints? I don't know if I can see. It might be difficult to
have a show of hands here. I think there's some comments. Okay, that's great. Did anybody
understand what that person was saying? I would expect not. So it's really actually,
although I said we are very good at understanding speech and background noise. That example
that I played you had a very high noise level. So actually the noise was had a higher intensity
than that target speech. But I want to give you a bit of a cue. So next I'll play you
another sentence by that same female target voice, but without background noise. So that's
of course easy to understand, but it will give us some idea of how that target voice
sounds like. A white silk jacket goes with any shoes.
All right, that's easy to understand. Now you have some idea basically, or we have some
Presenters
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01:13:52 Min
Aufnahmedatum
2021-06-04
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2021-06-04 16:38:15
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It’s great pleasure to welcome Prof. Dr. Tobias Reichenbach to FAU as a new professor after running a successful lab at Imperial College London!
Abstract: Understanding speech in noisy backgrounds requires selective attention to a particular speaker. Humans excel at this challenging task, while current speech recognition technology still struggles when background noise is loud. The neural mechanisms by which we process speech remain, however, poorly understood, not least due to the complexity of natural speech. Here we describe recent progress obtained through applying machine-learning to neuroimaging data of humans listening to speech in different types of background noise. In particular, we develop statistical models to relate characteristic features of speech such as pitch, amplitude fluctuations and linguistic surprisal to neural measurements. We find neural correlates of speech processing both at the subcortical level, related to the pitch, as well as at the cortical level, related to amplitude fluctuations and linguistic structures. We also show that some of these measures allow to diagnose disorders of consciousness. Our findings may be applied in smart hearing aids that automatically adjust speech processing to assist a user, as well as in the diagnosis of brain disorders.
Short Bio: Prof. Dr. Tobias Reichenbach (MSc Physics, Leipzig University; PhD Physics, LMU Munich) leads a research group on Sensory Neuroengineering at the Friedrich-Alexander-University (FAU) in Erlangen-Nuremberg. He previously worked with Kavli-Prize winner Prof. A. J. Hudspeth at the Rockefeller University, New York, and led a research group at Imperial College London. His multidisciplinary research combines methods from artificial intelligence with computational neuroscience and neuroimaging to advance our understanding of the neural processing of complex natural signals, with applications in medicine and technology. He has published more than 50 peer-reviewed articles, some of which have appeared in leading multidisciplinary journals such as Nature, Neuron and PNAS. Dr. Reichenbach is a Reviewing Editor for eLife, a renowned journal in the life sciences.
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Music Reference:
Damiano Baldoni - Thinking of You (Intro)
Damiano Baldoni - Poenia (Outro)