input: Text: PhD A: Alright. We're on. Professor B: Test, um. Test, test, test. Guess that's me. Yeah. OK. Grad D: Ooh, Thursday. Professor B: So. There's two sheets of paper in front of us. PhD A: What are these? PhD E: Yeah. So. Professor B: This is the arm wrestling? PhD C: Uh. Yeah, we formed a coalition actually. PhD E: Yeah. Almost. PhD C: We already made it into one. Professor B: Oh, good. PhD C: Yeah. Professor B: Excellent. PhD E: Yeah. Professor B: That's the best thing. PhD E: Mm - hmm. Professor B: So, tell me about it. PhD E: So it's <unk>disfmarker<unk> well, it's <unk>pause<unk> spectral subtraction or Wiener filtering, um, depending on if we put <unk>disfmarker<unk> if we square the transfer function or not. Professor B: Right. PhD E: And then with over - estimation of the noise, depending on the, uh <unk>disfmarker<unk> the SNR, with smoothing along time, um, smoothing along frequency. Professor B: Mm - hmm. PhD E: It's very simple, smoothing things. Professor B: Mm - hmm. PhD E: And, um, <unk>vocalsound<unk> the best result is <unk>vocalsound<unk> when we apply this procedure on FFT bins, uh, with a Wiener filter. Professor B: Mm - hmm. PhD E: And there is no noise addition after <unk>disfmarker<unk> after that. Professor B: OK. PhD E: So it's good because <unk>vocalsound<unk> <unk>vocalsound<unk> it's difficult when we have to add noise to <unk>disf
  Question: Summarize the meeting
  Answer:
output: The group discussed the current state of their work, which was coming close to a conclusion. They were putting together their final model, including the various techniques they had explored. Their performance on the Aurora tasks was second and very close to those in first place. The professor thought that further tweaking and incorporation of a neural network would improve their scores. The team discussed which method to use for noise suppression, which had not been decided yet. They also delved into a more detailed discussion of the VAD and latency. Their method for noise estimation would add a notable delay to the model. Finally, the team delved further into how to finish up the model.