10 citations · 26 across the 7 of their papers we have counts for
4 papers · 1 filter
Dialog+ in Broadcasting: First Field Tests Using Deep-Learning-Based Dialogue Enhancement
Matteo Torcoli, Christian Simon, Jouni Paulus +9
Difficulties in following speech due to loud background sounds are common in broadcasting. Object-based audio, e.g., MPEG-H Audio solves this problem by providing a user-adjustable…
Controlling the Perceived Sound Quality for Dialogue Enhancement with Deep Learning
Christian Uhle, Matteo Torcoli, Jouni Paulus
Speech enhancement attenuates interfering sounds in speech signals but may introduce artifacts that perceivably deteriorate the output signal. We propose a method for controlling t…
Controlling the Remixing of Separated Dialogue with a Non-Intrusive Quality Estimate
Matteo Torcoli, Jouni Paulus, Thorsten Kastner +1
Remixing separated audio sources trades off interferer attenuation against the amount of audible deteriorations. This paper proposes a non-intrusive audio quality estimation method…
A Hands-on Comparison of DNNs for Dialog Separation Using Transfer Learning from Music Source Separation
Martin Strauss, Jouni Paulus, Matteo Torcoli +1
This paper describes a hands-on comparison on using state-of-the-art music source separation deep neural networks (DNNs) before and after task-specific fine-tuning for separating s…