David Nahamoo — accepted AI-conference papers

2021

CNNBiF: CNN-based Bigram Features for Named Entity Recognition

Chul Sung, Vaibhava Goel, Etienne Marcheret, Steven Rennie, David Nahamoo

EMNLP 2021finding

Transformer models fine-tuned with a sequence labeling objective have become the dominant choice for named entity recognition tasks. However, a self-attention mechanism with unconstrained length can fail to fully capture local dependencies, particularly when training data is limited. In this paper,…

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2019

Head Related Impulse Response Interpolation and Extrapolation Using Deep Belief Networks

Grady Kestler, Shahrokh Yadegari, David Nahamoo

ICASSP 2019accepted

This paper presents a machine learning Deep Belief Network technique for interpolation and extrapolation of HRTF (Head Related Transfer Function) databases. In this technique, we decouple the stereo pair of HRTFs for each ear. Furthermore, we remove the inter-aural time differences (ITD) and distanc…

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