Study of speaker localization with binaural microphone array incorporating auditory filters and lateral angle estimation
arXiv:2310.20238 · doi:10.1016/j.apacoust.2023.109632
Abstract
Speaker localization for binaural microphone arrays has been widely studied for applications such as speech communication, video conferencing, and robot audition. Many methods developed for this task, including the direct path dominance (DPD) test, share common stages in their processing, which include transformation using the short-time Fourier transform (STFT), and a direction of arrival (DOA) search that is based on the head related transfer function (HRTF) set. In this paper, alternatives to these processing stages, motivated by human hearing, are proposed. These include incorporating an auditory filter bank to replace the STFT, and a new DOA search based on transformed HRTF as steering vectors. A simulation study and an experimental study are conducted to validate the proposed alternatives, and both are applied to two binaural DOA estimation methods; the results show that the proposed method compares favorably with current methods.
References in corpus (5)
- A Survey of Sound Source Localization with Deep Learning Methods
- Multi-Speaker DOA Estimation Using Deep Convolutional Networks Trained with Noise Signals
- Exploiting Deep Neural Networks and Head Movements for Robust Binaural Localisation of Multiple Sources in Reverberant Environments
- Estimation of the Direct-Path Relative Transfer Function for Supervised Sound-Source Localization
- Robust Binaural Localization of a Target Sound Source by Combining Spectral Source Models and Deep Neural Networks