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,
  Question: What were the topics talked about in the meeting?
  Answer:
output: The group discussed efforts to train and test the Aurora group's HTK-based recognition system on ICSI's digits corpus. Members also discussed efforts to produce forced alignments from a selection of Meeting Recorder data. Performance in both tasks was adversely affected by the manner of recording conditions implemented and difficulties attributing utterances to the appropriate speakers. While debugging efforts resulted in improved forced alignments, dealing with mixed channel speech and speaker overlap remains a key objective for future work. The group is additionally focused on a continued ability to feed different features into the recognizer and then train the system accordingly. 