Development of distant multi-channel speech and noise databases for speech recognition by in-door conversational robots
Young-Joo Suh, Younggwan Kim, Hyungjun Lim, Jahyun Goo, Youngmoon Jung, Yeonjoo Choi, Hoirin Kim, Dae-Lim Choi, Yong-Ju Lee
- 发表年份
- 2017
- 引用次数
- 6
摘要
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.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991