Papers by Roy Cohen
On the Semantic Latent Space of Diffusion-Based Text-To-Speech Models (2024.acl-short)
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| Challenge: | Denoising Diffusion Models (DDMs) are a powerful generative tool for text-to-speech (TTS) but their semantic capabilities are unknown and control of synthesized speech’s vocal properties remains a challenge. |
| Approach: | They explore the latent space of frozen TTS models composed of latent bottleneck activations of the DDM’s denoiser and propose methods for finding semantic directions within it. |
| Outcome: | The proposed methods enable off-the-shelf audio editing without any training, architectural changes or data requirements. |
RepGraph: Visualising and Analysing Meaning Representation Graphs (2021.emnlp-demo)
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| Challenge: | Graph-based meaning representations provide rich semantic annotations, but visualising them clearly is more challenging than for fully lexicalized representations. |
| Approach: | They propose to use RepGraph to visualise, manipulate and analyse semantically parsed graph data in a JSON-based serialisation format. |
| Outcome: | The proposed visualisation and analysis tool supports DMRS, EDS, PTG, UCCA, and AMR semantic frameworks. |