Multichannel Audio Front-End for Far-Field Automatic Speech Recognition
- Resource Type
- Conference
- Authors
- Chhetri, Amit; Hilmes, Philip; Kristjansson, Trausti; Chu, Wai; Mansour, Mohamed; Li, Xiaoxue; Zhang, Xianxian
- Source
- 2018 26th European Signal Processing Conference (EUSIPCO) Signal Processing Conference (EUSIPCO), 2018 26th European. :1527-1531 Sep, 2018
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Signal Processing and Analysis
Acoustics
Signal processing algorithms
Array signal processing
Engines
Measurement
Microphone arrays
Beamforming
far-field
AFE
deep neural networks
ASR
Amazon Echo
- Language
- ISSN
- 2076-1465
Far-field automatic speech recognition (ASR) is a key enabling technology that allows untethered and natural voice interaction between users and Amazon Echo family of products. A key component in realizing far-field ASR on these products is the suite of audio front-end (AFE) algorithms that helps in mitigating acoustic environmental challenges and thereby improving the ASR performance. In this paper, we discuss the key algorithms within the AFE, and we provide insights into how these algorithms help in mitigating the various acoustical challenges for far-field processing. We also provide insights into the audio algorithm architecture adopted for the AFE, and we discuss ongoing and future research.