Active noise cancellation on open-ear smart glasses
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866913009634377728 |
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| author | Yuan, Kuang Liu, Freddy Yifei Xiao, Tong Song, Yiwen Shen, Chengyi Bhutani, Saksham Chan, Justin Kumar, Swarun |
| author_facet | Yuan, Kuang Liu, Freddy Yifei Xiao, Tong Song, Yiwen Shen, Chengyi Bhutani, Saksham Chan, Justin Kumar, Swarun |
| contents | Smart glasses are becoming an increasingly prevalent wearable platform, with audio as a key interaction modality. However, hearing in noisy environments remains challenging because smart glasses are equipped with open-ear speakers that do not seal the ear canal. Furthermore, the open-ear design is incompatible with conventional active noise cancellation (ANC) techniques, which rely on an error microphone inside or at the entrance of the ear canal to measure the residual sound heard after cancellation. Here we present the first real-time ANC system for open-ear smart glasses that suppresses environmental noise using only microphones and miniaturized open-ear speakers embedded in the glasses frame. Our low-latency computational pipeline estimates the noise at the ear from an array of eight microphones distributed around the glasses frame and generates an anti-noise signal in real-time to cancel environmental noise. We develop a custom glasses prototype and evaluate it in a user study across 8 environments under mobility in the 100--1000 Hz frequency range, where environmental noise is concentrated. We achieve a mean noise reduction of 9.6 dB without any calibration, and 11.2 dB with a brief user-specific calibration. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_05519 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Active noise cancellation on open-ear smart glasses Yuan, Kuang Liu, Freddy Yifei Xiao, Tong Song, Yiwen Shen, Chengyi Bhutani, Saksham Chan, Justin Kumar, Swarun Audio and Speech Processing Human-Computer Interaction Machine Learning Sound Signal Processing Smart glasses are becoming an increasingly prevalent wearable platform, with audio as a key interaction modality. However, hearing in noisy environments remains challenging because smart glasses are equipped with open-ear speakers that do not seal the ear canal. Furthermore, the open-ear design is incompatible with conventional active noise cancellation (ANC) techniques, which rely on an error microphone inside or at the entrance of the ear canal to measure the residual sound heard after cancellation. Here we present the first real-time ANC system for open-ear smart glasses that suppresses environmental noise using only microphones and miniaturized open-ear speakers embedded in the glasses frame. Our low-latency computational pipeline estimates the noise at the ear from an array of eight microphones distributed around the glasses frame and generates an anti-noise signal in real-time to cancel environmental noise. We develop a custom glasses prototype and evaluate it in a user study across 8 environments under mobility in the 100--1000 Hz frequency range, where environmental noise is concentrated. We achieve a mean noise reduction of 9.6 dB without any calibration, and 11.2 dB with a brief user-specific calibration. |
| title | Active noise cancellation on open-ear smart glasses |
| topic | Audio and Speech Processing Human-Computer Interaction Machine Learning Sound Signal Processing |
| url | https://arxiv.org/abs/2604.05519 |