Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  propose a Direction of Arrival (DoA) estimator for a Hearing Aid System (HAS) which can connect to a wireless microphone worn by a target talker. The wireless microphone "informs" the HAS about the almost noise-free content of the target sound, and the proposed DoA estimator uses the knowledge of the noise-free target sound and the received microphone signals to estimate the DoA via a maximum likelihood approach. Moreover, the proposed DoA estimator resorts to a user-independent spherical-head model to consider the acoustic impacts of the head on the received signals at the HAS. Further, the proposed DoA estimator uses an Inverse Discrete Fourier Transform (IDFT) technique to evaluate the likelihood function computationally efficiently.  assessed the performance of the proposed estimator for various DoAs, Signal to Noise Ratios (SNRs), and target distances in different noisy and reverberant situations. The proposed estimator improves the performance markedly over other recently proposed "informed" DoA estimators.
['Mojtaba Farmani', 'Michael Syskind Pedersen', 'Zheng-Hua Tan', 'Jesper Jensen']
I am writing a research paper on a idea Informed Direction of Arrival estimation using a spherical-head model for Hearing Aid applications
[{"from": "human", "value": "I am writing a research paper on a idea Informed Direction of Arrival estimation using a spherical-head model for Hearing Aid applications"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  propose a Direction of Arrival (DoA) estimator for a Hearing Aid System (HAS) which can connect to a wireless microphone worn by a target talker. The wireless microphone \"informs\" the HAS about the almost noise-free content of the target sound, and the proposed DoA estimator uses the knowledge of the noise-free target sound and the received microphone signals to estimate the DoA via a maximum likelihood approach. Moreover, the proposed DoA estimator resorts to a user-independent spherical-head model to consider the acoustic impacts of the head on the received signals at the HAS. Further, the proposed DoA estimator uses an Inverse Discrete Fourier Transform (IDFT) technique to evaluate the likelihood function computationally efficiently.  assessed the performance of the proposed estimator for various DoAs, Signal to Noise Ratios (SNRs), and target distances in different noisy and reverberant situations. The proposed estimator improves the performance markedly over other recently proposed \"informed\" DoA estimators."}]