Improving Speech Attenuation in Headphones using Harmonic Model Decomposition and Multiple-Frequency ANC

In environments such as open offices, call centres, etc., speech is often the main disturbing source of ambient noise, reducing concentration and productivity. Active noise control (ANC) systems have difficulties in dealing with speech due to its non-stationary nature and constraints in the ANC system, which require the optimal filters to be non-causal. The non-causality is due to the delay incurred by, e.g., digital processing or acoustic propagation paths. To deal with this, we propose a new feedforward ANC system for headphone applications, HMD-ANC, which improves voiced speech attenuation. Notably, in HMD-ANC, each speech harmonic and its quadrature version, obtained by the harmonic model decomposition, are predicted by a two-weight adaptive filter to overcome the delay. The results show that HMD-ANC outperforms conventional adaptive feedforward ANC for delays starting from 6 samples (0.125 ms) at a sampling frequency of 48 kHz. Moreover, HMD-ANC extends the attenuation bandwidth, e.g., up to 2.5 kHz, while the conventional ANC is limited to 1 kHz.