input: Text: Grad E: OK, we're on. Professor B: OK. Grad E: So, I mean, everyone who's on the wireless check that they're on. PhD F: C we <unk>disfmarker<unk> Grad G: Alright. Postdoc C: I see. Yeah. PhD F: Yeah. Grad E: OK, our agenda was quite short. Professor B: Oh, could you <unk>pause<unk> close the door, maybe? Yeah. Grad E: Sure. Two items, which was, uh, digits and possibly stuff on <unk>disfmarker<unk> on, uh, forced alignment, which Jane said that Liz and Andreas had in information on, Professor B: Grad E: but they didn't, PhD F: Mm - hmm. Professor B: I guess the only other thing, uh, for which I <unk>disfmarker<unk> Grad E: so. PhD F: We should do that second, because Liz might join us in time for that. Grad E: OK. Professor B: Um. OK, so there's digits, alignments, and, um, I guess the other thing, <unk>vocalsound<unk> which I came unprepared for, uh, <unk>vocalsound<unk> is, uh, to dis s s see if there's anything anybody wants to discuss about the Saturday meeting. Grad E: Right. Professor B: So. Any <unk>disfmarker<unk> I mean, maybe not. Grad E: Digits and alignments. But <unk>disfmarker<unk> Professor B: Uh. PhD F: Talk about aligning people's schedules. Professor B: Yeah. Grad E: Yeah. Postdoc C: Mm - hmm. Professor B: Yeah. I mean <unk>disfmarker<unk> Right. Yeah, I mean, it was <unk>disfmarker<unk> Grad E: Yeah, it
  Question: What did PhD A say about overlaps?
  Answer:
output: The recognizer performed well on time-aligned segments labelled as 'non-overlap' (i.e. one person talking), while segments labelled as 'overlap' (i.e. multiple speakers talking at the same time) yielded poor results