# Onoma-to-wave: Environmental sound synthesis from onomatopoeic words

arXiv: https://arxiv.org/abs/2102.05872 · HTML: https://mlsanity.com/paper/2102.05872/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Feb 2021.

## Built on by (most cited first, 4 of 4)

- [AudioLDM 2: Learning Holistic Audio Generation with Self-supervised Pretraining](https://mlsanity.com/paper/2308.05734/) (2023)
- [Conditional Sound Generation Using Neural Discrete Time-Frequency Representation Learning](https://mlsanity.com/paper/2107.09998/) (2021)
- [Sketching With Your Voice: "Non-Phonorealistic" Rendering of Sounds via Vocal Imitation](https://mlsanity.com/paper/2409.13507/) (2024)
- [A Production-Oriented Framework for Evaluation of SFX Generation](https://mlsanity.com/paper/2607.09973/) (2026)

## Abstract (arXiv)

In this paper, we propose a framework for environmental sound synthesis from onomatopoeic words. As one way of expressing an environmental sound, we can use an onomatopoeic word, which is a character sequence for phonetically imitating a sound. An onomatopoeic word is effective for describing diverse sound features. Therefore, using onomatopoeic words for environmental sound synthesis will enable us to generate diverse environmental sounds. To generate diverse sounds, we propose a method based on a sequence-to-sequence framework for synthesizing environmental sounds from onomatopoeic words. We also propose a method of environmental sound synthesis using onomatopoeic words and sound event labels. The use of sound event labels in addition to onomatopoeic words enables us to capture each sound event's feature depending on the input sound event label. Our subjective experiments show that our proposed methods achieve higher diversity and naturalness than conventional methods using sound event labels.