# Towards Learning Fine-Grained Disentangled Representations from Speech

arXiv: https://arxiv.org/abs/1808.02939 · HTML: https://mlsanity.com/paper/1808.02939/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Aug 2018.

## Built on by (most cited first, 1 of 1)

- [Disentangling speech from surroundings with neural embeddings](https://mlsanity.com/paper/2203.15578/) (2022)

## Abstract (arXiv)

Learning disentangled representations of high-dimensional data is currently an active research area. However, compared to the field of computer vision, less work has been done for speech processing. In this paper, we provide a review of two representative efforts on this topic and propose the novel concept of fine-grained disentangled speech representation learning.