A machine learning approach for computationally and energy efficient speech enhancement in binaural hearing aids

机译：一种用于双耳助听器中计算和节能语音增强的机器学习方法

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摘要

A binaural speech enhancement algorithm that combines superdirective beamforming with time-frequency (TF) masking is proposed. Supervised machine learning is used to design a speechoise classifier that estimates the ideal binary mask (IBM), which is further softened to reduce musical noise. The method is energy-efficient in two ways: the computational complexity is limited and the wireless data transmission optimized. The experimental work demonstrates the ability of the method to increase the intelligibility of speech corrupted by different types of noise in low SNR scenarios.

机译：提出了一种结合超指向性波束成形和时频（TF）掩蔽的双耳语音增强算法。监督式机器学习用于设计语音/噪声分类器，以估计理想的二进制掩码（IBM），并对其进行进一步软化以减少音乐噪音。该方法在两种方面具有能源效率：计算复杂度受到限制，无线数据传输得到了优化。实验工作证明了该方法能够提高在低SNR情况下被不同类型的噪声破坏的语音的清晰度。

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《IEEE International Conference on Acoustics, Speech and Signal Processing》|2016年|6515-6519|共5页
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David Aylln; Roberto Gil-Pita; Manuel Rosa-Zurera;
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Binaural hearing aids; Machine learning; Speech enhancement; Time-frequency masking;

机译：双耳助听器;机器学习;语音增强;时频掩蔽;

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专利

1. Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms [J] . Marc R. Sch?dler, Anna Warzybok, Birger Kollmeier Trends in Hearing . 2018,第22期

机译：使用机器学习对听众群体的助听器益处进行客观预测：双耳降噪算法的语音识别性能
2. Enhancing the energy efficiency of wireless-communicated binaural hearing aids for speech separation driven by soft-computing algorithms [J] . R. Gil-Pita, L. Cuadra, E. Alexandre, Applied Soft Computing . 2012,第7期

机译：通过软计算算法提高无线双耳助听器语音分离的能效
3. A Supervised Speech Enhancement Method for Smartphone-Based Binaural Hearing Aids [J] . Sun Zhuoyi, Li Yingdan, Jiang Hanjun, IEEE transactions on biomedical circuits and systems . 2020,第5期

机译：基于智能手机的双耳助听器的监督语音增强方法
4. A machine learning approach for computationally and energy efficient speech enhancement in binaural hearing aids [C] . David Ayll??n, Roberto Gil-Pita, Manuel Rosa-Zurera IEEE International Conference on Acoustics, Speech and Signal Processing . 2016

机译：双耳助听辅助工具计算与节能语音增强的机器学习方法
5. A Combined Statistical and Machine Learning Approach For Single Channel Speech Enhancement [D] . Tseng, Hung-Wei 2015

机译：统计和机器学习相结合的单通道语音增强方法
6. Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms [O] . Marc R. Schädler, Anna Warzybok, Birger Kollmeier 2018

机译：使用机器学习对听众群体的助听器益处进行客观预测：双耳降噪算法的语音识别性能
7. Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms [O] . Marc R. Schädler, Anna Warzybok, Birger Kollmeier 2018

机译：使用机器学习跨听众团体的助听器益处的客观预测：语音识别性能与双耳降噪算法

A machine learning approach for computationally and energy efficient speech enhancement in binaural hearing aids

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