2022 - Research.com Rising Star of Science Award
Felix Weninger spends much of his time researching Speech recognition, Artificial intelligence, Recurrent neural network, Speech processing and Pattern recognition. The various areas that he examines in his Speech recognition study include Cognitive psychology and Noise. His Artificial intelligence study combines topics in areas such as Matrix decomposition and Natural language processing.
His Recurrent neural network study incorporates themes from Time delay neural network, Speech enhancement, Task and Word error rate. The Speech processing study combines topics in areas such as Feature, Feature vector, Context awareness, Pragmatics and Visualization. His study in Pattern recognition is interdisciplinary in nature, drawing from both Non-negative matrix factorization and Source separation.
The scientist’s investigation covers issues in Speech recognition, Artificial intelligence, Pattern recognition, Recurrent neural network and Non-negative matrix factorization. His work deals with themes such as Speech enhancement, Feature extraction and Feature, which intersect with Speech recognition. His Artificial intelligence research incorporates themes from Matrix decomposition and Natural language processing.
His Pattern recognition research includes elements of Autoencoder and Conversational speech. His Recurrent neural network research is multidisciplinary, relying on both Time delay neural network, Valence and Test set. His research investigates the connection between Non-negative matrix factorization and topics such as Source separation that intersect with issues in Blind signal separation and Singing.
His scientific interests lie mostly in Speech recognition, Artificial intelligence, Pattern recognition, Word error rate and Affect. The study incorporates disciplines such as Paralanguage and Artificial neural network in addition to Speech recognition. His work focuses on many connections between Artificial neural network and other disciplines, such as Fuzzy logic, that overlap with his field of interest in Emotion recognition.
His work in Artificial intelligence addresses issues such as Natural language processing, which are connected to fields such as Set. His research in Pattern recognition intersects with topics in End-to-end principle and Regularization. The concepts of his Affect study are interwoven with issues in Context, Non metric, Variation, Speech corpus and Hidden Markov model.
His primary scientific interests are in Speech recognition, Artificial intelligence, Artificial neural network, Emotion recognition and Fuzzy logic. His Speech recognition research is multidisciplinary, incorporating perspectives in Adaptation and Robustness. His Artificial intelligence research is multidisciplinary, incorporating elements of Stress, Mandarin Chinese and Identification.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Recent developments in openSMILE, the munich open-source multimedia feature extractor
Florian Eyben;Felix Weninger;Florian Gross;Björn Schuller.
acm multimedia (2013)
The INTERSPEECH 2013 computational paralinguistics challenge: social signals, conflict, emotion, autism
Björn W. Schuller;Stefan Steidl;Anton Batliner;Alessandro Vinciarelli.
conference of the international speech communication association (2013)
Speech Enhancement with LSTM Recurrent Neural Networks and its Application to Noise-Robust ASR
Felix Weninger;Hakan Erdogan;Shinji Watanabe;Emmanuel Vincent.
international conference on latent variable analysis and signal separation (2015)
Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures
John R. Hershey;Jonathan Le Roux;Felix Weninger.
arXiv: Learning (2014)
YouTube Movie Reviews: Sentiment Analysis in an Audio-Visual Context
M. Wollmer;F. Weninger;T. Knaup;B. Schuller.
IEEE Intelligent Systems (2013)
The INTERSPEECH 2012 Speaker Trait Challenge
Björn W. Schuller;Stefan Steidl;Anton Batliner;Elmar Nöth.
conference of the international speech communication association (2012)
Discriminatively trained recurrent neural networks for single-channel speech separation
Felix Weninger;John R. Hershey;Jonathan Le Roux;Bjorn Schuller.
ieee global conference on signal and information processing (2014)
Real-life voice activity detection with LSTM Recurrent Neural Networks and an application to Hollywood movies
Florian Eyben;Felix Weninger;Stefano Squartini;Bjorn Schuller.
international conference on acoustics, speech, and signal processing (2013)
On the Acoustics of Emotion in Audio: What Speech, Music, and Sound have in Common
Felix Weninger;Florian Eyben;Björn W. Schuller;Björn W. Schuller;Marcello Mortillaro.
Frontiers in Psychology (2013)
Introducing CURRENNT: the Munich open-source CUDA recurrent neural network toolkit
Felix Weninger;Johannes Bergmann;Björn Schuller.
Journal of Machine Learning Research (2015)
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