This paper presents our newly developed real-time meeting analyzer for monitoring conversations in an ongoing group meeting. The goal of the system is to automatically recognize "who is speaking what" in an online manner for meeting assistance. Our system continuously captures the utterances and the face pose of each speaker using a distant microphone array and an omni-directional camera at the center of the meeting table. Through a series of advanced audio processing operations, an overlapping speech signal is enhanced and the components are separated into individual speaker's channels. Then the utterances are sequentially transcribed by our speech recognizer with low latency. In parallel with speech recognition, the activity of each participant (e.g. speaking, laughing, watching someone) and the situation of the meeting (e.g. topic, activeness, casualness) are detected and displayed on a browser together with the transcripts. In this paper, we describe our techniques and our attempt to achieve the low-latency monitoring of meetings, and we show our experimental results for real-time meeting transcription.