Development of distant multi-channel speech and noise databases for speech recognition by in-door conversational robots

Abstract

In this paper, we presents the method and procedure for collecting the Korean distant multi-channel speech and noise databases, which were designed for developing the highly accurate distant speech recognition system for indoor conversational robot applications. The speech database was collected at four different distant positions in an in-door room, which was furnished to simulate a living room acoustically, by the playback-and-recording method that uses an artificial mouth for playing the clean source speech data and three kinds of multi-channel microphone arrays for recording the distant speech data. The speech database further consists of a read speech dataset and two conversational speech datasets. Additionally, the noise database consists of 12 types of in-door noise, which were collected at a single distant position with the same approach. These speech and noise databases can be used for creating simulated noisy speech data reflecting various in-door acoustic conditions corrupted by room reverberation and additive noise.