input: Text: PhD F: And we're on. Professor D: OK. Might wanna <unk>vocalsound<unk> close the door so that <unk>disfmarker<unk> Uh, Stephane will <unk>disfmarker<unk> PhD F: I 'll get it. Professor D: Yeah PhD F: Hey Dave? Could you go ahead and turn on, uh, Stephane's <unk>disfmarker<unk> Grad C: Mm - hmm. Professor D: So that's the virtual Stephane over there. PhD F: OK. Professor G: Do you use a PC for recording? Or <unk>disfmarker<unk> PhD F: Uh, yeah, a Linux box. Yeah. It's got, uh, like sixteen channels going into it. Professor G: Uh - huh. Uh - huh. The quality is quite good? Or <unk>disfmarker<unk>? PhD F: Mm - hmm. Yeah, so far, it's been pretty good. Professor G: Mm - hmm. Professor D: Yeah. So, uh, yeah <unk>disfmarker<unk> the suggestion was to have these guys start to <unk>disfmarker<unk> PhD F: OK. Why don't you go ahead, Dave? Grad C: OK. Um, so, yeah, the <unk>disfmarker<unk> this past week I've been main mainly occupied with, um, getting some results, u from the SRI system trained on this short Hub - five training set for the mean subtraction method. And, um, I ran some tests last night. But, um, c the results are suspicious. Um, it's, um, <unk>vocalsound<unk> cuz they're <unk>disfmarker<unk> the baseline results are worse than, um, Andreas <unk>disfmarker<unk> than results Andreas got previously. And
  Question: What did professor G say about smoothing?
  Answer:
output: Professor G was trying to understand where the smoothing took place in PhD B's model. Professor G suggested that the smoothing was best done as early as possible.