An intelligent meeting recording system for BoBi secretary robot

This paper presents an intelligent meeting recording system for an intelligent personal robot named BoBi secretary. Participants register their voices to the system before meeting. In meeting, a Microphone records voice while applying another process to recognize the voice at the same time to transform it into text resulting in an online meeting recording. The speech of the meeting recording system includes voices of multiple speakers, and it is necessary to divide it into parts of speakers before recognizing them and applying speech recognition. We attempt two methods to recognize the meeting voice: segmentation-based method and segmentation-free method. The segmentation-based method applies a Voice Activity Detection (VAD) algorithm to detect the speech and the non-speech frames to segment the recorded voice into speaker parts. Then it applies Gaussian Mixture Models (GMMs) to Mel-Frequency Cepstral Coefficient (MFCC) features extracted from each part to recognize which speaker it is from. The segmentation-free method evaluates the voice frames using MFCC features and GMMs, and then searches the optimal path as the segmentation result into the voice frames lattice. Finally each speaker's voice is sent to a speech recognition server to obtain a result text. We make a comparison between meeting recording system using segmentation-free method and that using segmentation-based method, and show the result that the segmentation-based method brings better result.