A Systematic Comparison of Phonetic Aware Techniques for Speech Enhancement. (arXiv:2206.11000v1 [eess.AS])

Web: http://arxiv.org/abs/2206.11000

Speech enhancement has seen great improvement in recent years using
end-to-end neural networks. However, most models are agnostic to the spoken
phonetic content. Recently, several studies suggested phonetic-aware speech
enhancement, mostly using perceptual supervision. Yet, injecting phonetic
features during model optimization can take additional forms (e.g., model
conditioning). In this paper, we conduct a systematic comparison between
different methods of incorporating phonetic information in a speech enhancement
model. By conducting a series of controlled experiments, we observe the
influence of …

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