5 citations · 6 across the 3 of their papers we have counts for
5 papers
Investigation into Target Speaking Rate Adaptation for Voice Conversion
Michael Kuhlmann, Fritz Seebauer, Janek Ebbers +2
Disentangling speaker and content attributes of a speech signal into separate latent representations followed by decoding the content with an exchanged speaker representation is a…
Threshold Independent Evaluation of Sound Event Detection Scores
Janek Ebbers, Romain Serizel, Reinhold Haeb-Umbach
Performing an adequate evaluation of sound event detection (SED) systems is far from trivial and is still subject to ongoing research. The recently proposed polyphonic sound detect…
Voice Conversion Based Speaker Normalization for Acoustic Unit Discovery
Thomas Glarner, Janek Ebbers, Reinhold Häb-Umbach
Discovering speaker independent acoustic units purely from spoken input is known to be a hard problem. In this work we propose an unsupervised speaker normalization technique prior…
Forward-Backward Convolutional Recurrent Neural Networks and Tag-Conditioned Convolutional Neural Networks for Weakly Labeled Semi-supervised Sound Event Detection
Janek Ebbers, Reinhold Haeb-Umbach
In this paper we present our system for the detection and classification of acoustic scenes and events (DCASE) 2020 Challenge Task 4: Sound event detection and separation in domest…
Contrastive Predictive Coding Supported Factorized Variational Autoencoder for Unsupervised Learning of Disentangled Speech Representations
Janek Ebbers, Michael Kuhlmann, Tobias Cord-Landwehr +1
In this work we address disentanglement of style and content in speech signals. We propose a fully convolutional variational autoencoder employing two encoders: a content encoder a…