# ISAC: An Invertible and Stable Auditory Filter Bank with Customizable Kernels for ML Integration

arXiv: https://arxiv.org/abs/2505.07709 · HTML: https://mlsanity.com/paper/2505.07709/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 16 of its 33 references that are in the map.
- First posted on arXiv 12 May 2025.

## Builds on (most cited first, 16 of 16)

- [wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations](https://mlsanity.com/paper/2006.11477/) (2020)
- [WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing](https://mlsanity.com/paper/2110.13900/) (2021)
- [Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation](https://mlsanity.com/paper/1809.07454/) (2018)
- [Parseval Networks: Improving Robustness to Adversarial Examples](https://mlsanity.com/paper/1704.08847/) (2017)
- [Speaker Recognition from Raw Waveform with SincNet](https://mlsanity.com/paper/1808.00158/) (2018)
- [LEAF: A Learnable Frontend for Audio Classification](https://mlsanity.com/paper/2101.08596/) (2021)
- [Learning Filterbanks from Raw Speech for Phone Recognition](https://mlsanity.com/paper/1711.01161/) (2017)
- [Data augmentation and loss normalization for deep noise suppression](https://mlsanity.com/paper/2008.06412/) (2020)
- [Spectral Leakage and Rethinking the Kernel Size in CNNs](https://mlsanity.com/paper/2101.10143/) (2021)
- [FastAudio: A Learnable Audio Front-End for Spoof Speech Detection](https://mlsanity.com/paper/2109.02774/) (2021)
- [Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras](https://mlsanity.com/paper/1706.05781/) (2017)
- [DNN Filter Bank Cepstral Coefficients for Spoofing Detection](https://mlsanity.com/paper/1702.03791/) (2017)
- [(Almost) Smooth Sailing: Towards Numerical Stability of Neural Networks Through Differentiable Regularization of the Condition Number](https://mlsanity.com/paper/2410.00169/) (2024)
- [Instabilities in Convnets for Raw Audio](https://mlsanity.com/paper/2309.05855/) (2023)
- [Hold Me Tight: Stable Encoder-Decoder Design for Speech Enhancement](https://mlsanity.com/paper/2408.17358/) (2024)
- [Designing Gabor windows using convex optimization](https://mlsanity.com/paper/1401.6033/) (2014)

## Abstract (arXiv)

This paper introduces ISAC, an invertible and stable, perceptually-motivated filter bank that is specifically designed to be integrated into machine learning paradigms. More precisely, the center frequencies and bandwidths of the filters are chosen to follow a non-linear, auditory frequency scale, the filter kernels have user-defined maximum temporal support and may serve as learnable convolutional kernels, and there exists a corresponding filter bank such that both form a perfect reconstruction pair. ISAC provides a powerful and user-friendly audio front-end suitable for any application, including analysis-synthesis schemes.