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Found 4 papers, 3 papers with code
Neural Text Sanitization with Privacy Risk Indicators: An Empirical Analysis
The text sanitization process starts with a privacy-oriented entity recognizer that seeks to determine the text spans expressing identifiable personal information.
Bootstrapping Text Anonymization Models with Distant Supervision
Instead of requiring manually labeled training data, the approach relies on a knowledge graph expressing the background information assumed to be publicly available about various individuals.
The Text Anonymization Benchmark (TAB): A Dedicated Corpus and Evaluation Framework for Text Anonymization
We present a novel benchmark and associated evaluation metrics for assessing the performance of text anonymization methods.
RNNoise-Ex: Hybrid Speech Enhancement System based on RNN and Spectral Features
Recent interest in exploiting Deep Learning techniques for Noise Suppression, has led to the creation of Hybrid Denoising Systems that combine classic Signal Processing with Deep Learning.
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