Transformers are powerful neural architectures that allow integrating different modalities
using attention mechanisms. In this paper, we leverage the neural transformer architectures …

The traditional generalized sidelobe canceller (GSC) is a common speech enhancement
front end to improve the noise robustness of automatic speech recognition (ASR) systems in …

Multi-channel inputs offer several advantages over single-channel, to improve the
robustness of on-device speech recognition systems. Recent work on multi-channel …

Self-supervised speech pre-training methods have developed rapidly in recent years, which
show to be very effective for many near-field single-channel speech tasks. However, far-field …

Conventional speech enhancement technique such as beamforming has known benefits for
far-field speech recognition. Our own work in frequency-domain multi-channel acoustic …

In this paper, we propose a dual-encoder ASR architecture for joint modeling of close-talk
(CT) and far-talk (FT) speech, in order to combine the advantages of CT and FT devices for …

Automatic speech recognition (ASR) in challenging conditions, such as in the presence of
interfering speakers or music, remains an unsolved problem. This paper presents Extract …

With the development of teleconferencing and in-vehicle voice assistants, far-field multi-
speaker speech recognition has become a hot research topic. Recently, a multi-channel …

The elastic spatial filter (ESF) proposed in recent years is a popular multi-channel speech
enhancement front end based on deep neural network (DNN). It is suitable for real-time …

Automatic speech recognition (ASR) in the cloud allows the use of larger models and more
powerful multi-channel signal processing front-ends compared to on-device processing …