# Low-frequency Compensated Synthetic Impulse Responses for Improved Far-field Speech Recognition

arXiv: https://arxiv.org/abs/1910.10815 · HTML: https://mlsanity.com/paper/1910.10815/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Oct 2019.

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

- [Synthetic Wave-Geometric Impulse Responses for Improved Speech Dereverberation](https://mlsanity.com/paper/2212.05360/) (2022)

## Abstract (arXiv)

We propose a method for generating low-frequency compensated synthetic impulse responses that improve the performance of far-field speech recognition systems trained on artificially augmented datasets. We design linear-phase filters that adapt the simulated impulse responses to equalization distributions corresponding to real-world captured impulse responses. Our filtered synthetic impulse responses are then used to augment clean speech data from LibriSpeech dataset [1]. We evaluate the performance of our method on the real-world LibriSpeech test set. In practice, our low-frequency compensated synthetic dataset can reduce the word-error-rate by up to 8.8% for far-field speech recognition.