4 citations · 10 across the 4 of their papers we have counts for
9 papers
SpeechPainter: Text-conditioned Speech Inpainting
Zalán Borsos, Matt Sharifi, Marco Tagliasacchi
We propose SpeechPainter, a model for filling in gaps of up to one second in speech samples by leveraging an auxiliary textual input. We demonstrate that the model performs speech…
Data Summarization via Bilevel Optimization
Zalán Borsos, Mojmír Mutný, Marco Tagliasacchi +1
The increasing availability of massive data sets poses a series of challenges for machine learning. Prominent among these is the need to learn models under hardware or human resour…
MicAugment: One-shot Microphone Style Transfer
Zalán Borsos, Yunpeng Li, Beat Gfeller +1
A crucial aspect for the successful deployment of audio-based models "in-the-wild" is the robustness to the transformations introduced by heterogeneous acquisition conditions. In t…
Semi-supervised Batch Active Learning via Bilevel Optimization
Zalán Borsos, Marco Tagliasacchi, Andreas Krause
Active learning is an effective technique for reducing the labeling cost by improving data efficiency. In this work, we propose a novel batch acquisition strategy for active learni…
Coresets via Bilevel Optimization for Continual Learning and Streaming
Zalán Borsos, Mojmír Mutný, Andreas Krause
Coresets are small data summaries that are sufficient for model training. They can be maintained online, enabling efficient handling of large data streams under resource constraint…
Transfer NAS: Knowledge Transfer between Search Spaces with Transformer Agents
Zalán Borsos, Andrey Khorlin, Andrea Gesmundo
Recent advances in Neural Architecture Search (NAS) have produced state-of-the-art architectures on several tasks. NAS shifts the efforts of human experts from developing novel arc…