Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   investigate an Adaptive Line Enhancer (ALE) for the cancellation of robot self-noise. In contrast to many other methods, it requires only a single microphone and can be combined with any other single- and multi-channel noise reduction method. The proposed ALE is implemented in the frequency domain (FDALE) and performs noise cancellation with respect to magnitude and phase. It therefore has the potential to reduce noise components without introducing distortions of the target signal.  combine the ALE with a traditional single-channel noise reduction filter, where the former cancels predictable noise components and the latter suppresses the random noise components.  apply this approach to an automatic speech recognition task and show that significant improvements can be obtained.
['Jalal Taghia', 'Dorothea Kolossa', 'Rainer Martin']
I am writing a research paper on a idea ALE for robots! A single-channel approach to robot self-noise cancellation
[{"from": "human", "value": "I am writing a research paper on a idea ALE for robots! A single-channel approach to robot self-noise cancellation"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   investigate an Adaptive Line Enhancer (ALE) for the cancellation of robot self-noise. In contrast to many other methods, it requires only a single microphone and can be combined with any other single- and multi-channel noise reduction method. The proposed ALE is implemented in the frequency domain (FDALE) and performs noise cancellation with respect to magnitude and phase. It therefore has the potential to reduce noise components without introducing distortions of the target signal.  combine the ALE with a traditional single-channel noise reduction filter, where the former cancels predictable noise components and the latter suppresses the random noise components.  apply this approach to an automatic speech recognition task and show that significant improvements can be obtained."}]