Path: utzoo!utgpu!news-server.csri.toronto.edu!rpi!zaphod.mps.ohio-state.edu!samsung!rex!uflorida!mlb.semi.harris.com!trantor.harris-atd.com!x102a!mlaprade From: mlaprade@x102a.harris-atd.com (laprade maria 42641) Newsgroups: comp.dsp Subject: speech + noise Message-ID: <6003@trantor.harris-atd.com> Date: 5 Apr 91 13:47:28 GMT Sender: news@trantor.harris-atd.com Reply-To: mlaprade@x102a.ess.harris.com (laprade maria 42641) Distribution: all Organization: Harris Corporation GSS, Melbourne, Florida Lines: 26 I have a clean speaker database where I use the following to extract features: use energy and zero crossing to find voiced speech, pre-emphasize and high pass filter, autocorrelate. I was satisfied with those results and decided to add noise. I added white noise and processed it exactly the same way. For most of the speakers I have lost about half the number of features extracted ( I think I'm losing them because the pitch is calculated as a too high frequency. I do know that the zero crossing value has now doubled, and the energy threshold has increased about 100x for a SNR of 10dB.) Which I thought was reasonable. However I am left with less than 10 samples for 1 particular speaker. My question is am I incorrect to add in white noise, or do I need to modify my processing equations. I'm neither a speech nor a signal processing type engineer, I just need a database to feed to my neural network so please be explicit with your help. Thanks. -- Maria Laprade ARPA: mlaprade@x102a.harris-atd.com Harris Corporation - GASD UUCP: ...uunet!x102a!mlaprade Palm Bay, Florida voice: (407)727-4920