Meeting Decision Tracker: Making Meeting Minutes with De-Contextualized Utterances (2022)

Abstract: Meetings are a universal process to make decisions in business and project collaboration. The capability to automatically itemize the decisions in daily meetings allows for extensive tracking of past discussions. To that end, we developed Meeting Decision Tracker, a prototype system to construct decision items comprising decision utterance detector (DUD) and decision utterance rewriter (DUR). We show that DUR makes a sizable contribution to improving the user experience by dealing with utterance collapse in natural conversation. An introduction video of our system is also available at https://youtu.be/TG1pJJo0Iqo .

## introduction obtaining a brief description and salient contents of meetings is a functionality that can certainly help business operations. although automatic speech recognition enables us to transcribe meeting records automatically, its transcription is possibly much more verbose, noisy, or collapsed, and is far from being utilized in its raw form. previous research attempted to extract important information from dialogue, such as decision-making utterances, @xcite , extractive summaries of online forums @xcite , or group chat threads @xcite . another study, @xcite presented a discussion tracker to facilitate collaborative argumentation in classroom discussion by visualizing discussion transcription. however, extracted utterances are usually incomplete and difficult to understand due to ellipses and co-references in conversations @xcite . figure 1 (the right) shows an example of a partial dialogue ending with a decision-related utterance in our dataset. this shows that objects or indicatives in utterances in natural conversations are usually ambiguous, and the meaning of decision-related utterances has a strong dependency on context. furthermore, especially in japanese, the format of the spoken language is often far apart from the written language because of frank expressions and many filler phrases. this nature reduces user experience with the naive use of utterances extracted from dialogues. in response to this, incomplete utterance restoration (iur) @xcite @xcite handles the problem where the model rewrites and restores incomplete utterances by considering the dialogue context with promising results. however, we have yet to see iur models applied for practical use in actual business applications. this paper presents meeting decision tracker (mdt), a system that automatically generates the itemized decision list from meeting transcription. given the meeting transcription, mdt detects decision-making utterances and rewrites them to the de-contextualized utterance, i.e., the written form with omissions restoration and filler removal. such a capability allows users to look back at the previous meeting contents quickly and have asynchronous communication with no effort from a minute taker. the system has three crucial characteristics. the overall system architecture of meeting decision tracker (mdt) is depicted in figure 1 (the left). the main function of mdt is to generate decision items with de-contextualized representations from the transcription of daily business meetings. mdt comprises of two modules: decision utterance detector (dud) and decision utterance rewriter (dur). the detector extracts a decision list from meeting transcription and the rewriter translates (rewrites) the list to the written format. figure 1 (the right) shows the example pair of the input and expected output for the system. the example indicates two points. first, the transcription contains decision-related utterances that can be used to summarize the content of the meeting. second, the decision utterance itself is usually not self-consistent and comprehensible only after the utterance is restored by dur. the next sections introduce the detector and rewriter. ## evaluation in this section, we first show data annotation for the detector and rewriter, and then describe the settings used for experiments. we finally report the results and discussion of the detector and rewriter. ## demonstration scenario we provide a ui foot_4 that allows users to look back at decision-making items in past meetings at a glance. especially in business settings, the accumulation of daily meetings can be compactly stored as itemized decisions to be accessed easily and support project progress management and sharing. figure 2 shows an example processed by our system. the original decision-related utterance is highlighted in blue in figure 2c . its content "well, i wonder if we can trust the number of, uh, prerequisites come this month, well, we'll check on the number of containers to be replaced." is rewritten and displayed in the first line of the decision list in figure 2b as the de-contextualized form, "once the prerequisites for processing at the sapporo site arrive, the number of containers to be replaced should be confirmed..". the view of the first run is the list of the meetings uploaded (figure 2a ). when users click on the meeting from the list they intend to go back, so decision items for corresponding meeting are unfolded (figure 2b ). here we display de-contextualized decision by dur instead of original decision-related utterances. since the dur module makes decisionrelated utterances self-contained in the written language format, displayed decision items are straightforward and user-friendly to quickly understand them. to allow users to see the context of the discussion, users can click on the decision item and view the original transcription with a scrolling position where the corresponding decision-related utterance is at the bottom (figure 2c ). ## conclusion and future work in this paper, we presented meeting decision tracker, a system to automatically itemise the decision-making in daily meetings as well as the tracking of past discussions. we showed the effective adaptation of iur for decision-item tracking in the context of actual business scenarios. mdt not only displays itemized decision-utterances with an easy-to-understand format, but also allows users to go back and review the contextual dialogue deriving for the decision. future work will firstly improve the quality of the detector and rewriter. other potential directions will incorporate asr into mdt to create an end-to-end system and add functions to remind users of detected decisions and to search for past meetings.