Subject: Re: formant filtering From: "John K. Bates" <jkbates(at)COMPUTER.NET> Date: Mon, 3 Mar 2003 11:34:35 -0500Dear Eckard, There was a most interesting coincidence concerning your remarks on removing the "annoying highly tonal noise" caused by a pulsed arc welding process. Before seeing your note I had conducted an experiment on the pulsed arc waveform example (S1.wav) that you sent me just a year ago. (Ref. M197 and M202) This might be the same example you referred to in your note below. What happened was that while using this waveform to test my method for identifying time-domain features I found a way to remove its tonal components. As you may remember, I have been using my waveform information vector (WIV) method to select and identify impulsive sounds. The purpose of this method, as I have described it in previous communications, (M34) is to circumvent the well-known difficulties inherent in resolving spectral features of wideband impulses. At its basic level the WIV method can separate impulses from reverberations and background sound. Recently I have improved the algorithm to display in real time the semantic relationships of various classes of impulsive sounds. (For example, "boom," "pop," "click," etc.) My system obtains identifiable features of impulses based on waveform zeros. Each impulse is segmented at its onset and offset. Sequences of zeros that represent meaningful waveform features are transformed into two-dimensional patterns that are converted instantaneously into templates. These templates are progressively collected in a multidimensional array that relates classes of waveshapes to semantic meanings. The array method permits instantaneous recognition of repetitions of impulse patterns. For an evaluation of the system's operation in a really difficult impulsive sound environment I decided to use the impulsive complexity of your welding sounds. The S1.wav was especially interesting because it contains the "frying" sound of the welding process that is mixed with the tonal features of the arc's periodic repetition. It was while running tests to see what portions of the sound would be recognized when using templates having particular feature patterns that I discovered I could remove the tonal sounds from the welding sounds. This experiment, among many others, has shown that components of a complex acoustic environment can be selected and separated in the time domain. It also demonstrates that separating sounds by the WIV method avoids the limitations of spectral bandwidth. If tonal annoyance is still a pervasive problem in arc welding this method might be of value in removing such interference. Conversely, it could be useful for automatically monitoring particular sounds of the welding process. I regard these experiments on impulses as the starting point for developing a way to recognize, classify, and separate sounds in stages of increasing degrees of complexity which could culminate in truly robust speech recognition. My plan has been to get useful results by _not_ trying to imitate cochlear or neural functions. But that's another story. (See M115) John Bates >This difficulty to have an adequate basis for comparison reminds me of own >experience. We tried to use spectral smearing for mitigation of an annoying >highly tonal noise which was caused from a pulsed arc due to precise power >electronic switching. The method can avoid dangerous mechanical resonance. >We were also able to make the acoustic noise less 'cutting'. However, this >required to randomize frequency over a considerable range of deviation from >its technologically required mean value. We achieved a satisfactory >decrease of tonality only on condition this range exceeded the critical >bandwidth, while in this case the noise did perhaps not get less annoying >but, as expected, even louder. > >Eckard