67 citations · 344 across the 35 of their papers we have counts for
5 papers · 1 filter
DEPA: Self-Supervised Audio Embedding for Depression Detection
Pingyue Zhang, Mengyue Wu, Heinrich Dinkel +1
Depression detection research has increased over the last few decades, one major bottleneck of which is the limited data availability and representation learning. Recently, self-su…
Audio Caption in a Car Setting with a Sentence-Level Loss
Xuenan Xu, Heinrich Dinkel, Mengyue Wu +1
Captioning has attracted much attention in image and video understanding while a small amount of work examines audio captioning. This paper contributes a Mandarin-annotated dataset…
Text-based depression detection on sparse data
Heinrich Dinkel, Mengyue Wu, Kai Yu
Previous text-based depression detection is commonly based on large user-generated data. Sparse scenarios like clinical conversations are less investigated. This work proposes a te…
Duration robust weakly supervised sound event detection
Heinrich Dinkel, Kai Yu
Task 4 of the DCASE2018 challenge demonstrated that substantially more research is needed for a real-world application of sound event detection. Analyzing the challenge results it…
Audio Caption: Listen and Tell
Mengyue Wu, Heinrich Dinkel, Kai Yu
Increasing amount of research has shed light on machine perception of audio events, most of which concerns detection and classification tasks. However, human-like perception of aud…