67 citations · 344 across the 35 of their papers we have counts for
6 papers · 1 filter
CED: Consistent ensemble distillation for audio tagging
Heinrich Dinkel, Yongqing Wang, Zhiyong Yan +2
Augmentation and knowledge distillation (KD) are well-established techniques employed in audio classification tasks, aimed at enhancing performance and reducing model sizes on the…
AV-SepFormer: Cross-Attention SepFormer for Audio-Visual Target Speaker Extraction
Jiuxin Lin, Xinyu Cai, Heinrich Dinkel +7
Visual information can serve as an effective cue for target speaker extraction (TSE) and is vital to improving extraction performance. In this paper, we propose AV-SepFormer, a Sep…
Focus on the Sound around You: Monaural Target Speaker Extraction via Distance and Speaker Information
Jiuxin Lin, Peng Wang, Heinrich Dinkel +6
Previously, Target Speaker Extraction (TSE) has yielded outstanding performance in certain application scenarios for speech enhancement and source separation. However, obtaining au…
Understanding temporally weakly supervised training: A case study for keyword spotting
Heinrich Dinkel, Weiji Zhuang, Zhiyong Yan +3
The currently most prominent algorithm to train keyword spotting (KWS) models with deep neural networks (DNNs) requires strong supervision i.e., precise knowledge of the spoken key…
Streaming Audio Transformers for Online Audio Tagging
Heinrich Dinkel, Zhiyong Yan, Yongqing Wang +3
Transformers have emerged as a prominent model framework for audio tagging (AT), boasting state-of-the-art (SOTA) performance on the widely-used Audioset dataset. However, their im…
Unified Keyword Spotting and Audio Tagging on Mobile Devices with Transformers
Heinrich Dinkel, Yongqing Wang, Zhiyong Yan +2
Keyword spotting (KWS) is a core human-machine-interaction front-end task for most modern intelligent assistants. Recently, a unified (UniKW-AT) framework has been proposed that ad…