Zobrazeno 1 - 10
of 57
pro vyhledávání: '"Martin Wöllmer"'
Autor:
Florian Eyben, Martin Wöllmer, Tony Poitschke, Björn Schuller, Christoph Blaschke, Berthold Färber, Nhu Nguyen-Thien
Publikováno v:
Advances in Human-Computer Interaction, Vol 2010 (2010)
Besides reduction of energy consumption, which implies alternate actuation and light construction, the main research domain in automobile development in the near future is dominated by driver assistance and natural driver-car communication. The abili
Externí odkaz:
https://doaj.org/article/a6a912e2cfbc420faaf5212c8b6d3973
Publikováno v:
ASRU
This paper introduces a novel graphical model architecture for robust and vocabulary independent keyword spotting which does not require the training of an explicit garbage model. We show how a graphical model structure for phoneme recognition can be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f08219bdbf49e59b4c88aa2ff09c35e5
https://opus.bibliothek.uni-augsburg.de/opus4/files/76617/76617.pdf
https://opus.bibliothek.uni-augsburg.de/opus4/files/76617/76617.pdf
Publikováno v:
ACII
Various open-source toolkits exist for speech recognition and speech processing. These toolkits have brought a great benefit to the research community, i.e. speeding up research. Yet, no such freely available toolkit exists for automatic affect recog
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62faf346e9d2351c327af7174e1978f3
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/76611
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/76611
Publikováno v:
ICASSP
This paper proposes a novel system for robust keyword detection in continuous speech. Our decoder is composed of a bidirectional Long Short-Term Memory recurrent neural network using a Connectionist Temporal Classification (CTC) output layer, and a D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6c5523ef3fcc4d0e090ee5f9ae6a8a3a
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/76478
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/76478
To overcome the computational complexity of the asynchronous hidden Markov model (AHMM), we present a novel multidimensional dynamic time warping (DTW) algorithm for hybrid fusion of asynchronous data. We show that our newly introduced multidimension
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::69f5dd59ac08bb73fa26ce321f7c170b
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/76484
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/76484
For many applications of emotion recognition, such as virtual agents, the system must select responses while the user is speaking. This requires reliable on-line recognition of the user’s affect. However most emotion recognition systems are based o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7de63ffbf8f429bdd2d73ed8a958ab4f
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/76322
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/76322
Robustly detecting keywords in human speech is an important precondition for cognitive systems, which aim at intelligently interacting with users. Conventional techniques for keyword spotting usually show good performance when evaluated on well artic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64a8797184546ee602aa63ac92949900
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/76284
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/76284
Autor:
Björn Schuller, Luis Roalter, Matthias Kranz, Dejan Arsićc, Gerhard Rigoll, Florian Eyben, Moritz Kaiser, Martin Wöllmer
Publikováno v:
MPVA@MM
Virtual reality applications are emerging into various regions of research and entertainment. Although visual and acoustic capabilities are already quite impressive, a wide range of users still criticizes the user interface. Frequently complex and ve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::031b3c2e897e7cc0170b0a2efdedcbbd
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/76206
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/76206
Autor:
B Trefflich, Martin Wöllmer, T. Schindl, S Mayer, Berthold Färber, Björn Schuller, C. Blaschke
Lane-keeping assistance systems for vehicles may be more acceptable to users if the assistance was adaptive to the driver's state. To adapt systems in this way, a method for detection of driver distraction is needed. Thus, we propose a novel techniqu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d76d923386fa9aeb340836d41a9d931a
https://opus.bibliothek.uni-augsburg.de/opus4/files/73306/73306.pdf
https://opus.bibliothek.uni-augsburg.de/opus4/files/73306/73306.pdf
Highly spontaneous, conversational, and potentially emotional and noisy speech is known to be a challenge for today’s automatic speech recognition (ASR) systems, which highlights the need for advanced algorithms that improve speech features and mod
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::56499c4995c9664c6b0644aeb0bc330e
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/73303
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/73303