Deep learning for environmentally robust speech recognition: An overview of recent developments
Eliminating the negative effect of non-stationary environmental noise is a long-standing
research topic for automatic speech recognition but still remains an important challenge …
research topic for automatic speech recognition but still remains an important challenge …
Adaptation algorithms for neural network-based speech recognition: An overview
We present a structured overview of adaptation algorithms for neural network-based speech
recognition, considering both hybrid hidden Markov model/neural network systems and end …
recognition, considering both hybrid hidden Markov model/neural network systems and end …
Conditional diffusion probabilistic model for speech enhancement
Speech enhancement is a critical component of many user-oriented audio applications, yet
current systems still suffer from distorted and unnatural outputs. While generative models …
current systems still suffer from distorted and unnatural outputs. While generative models …
CHiME-6 challenge: Tackling multispeaker speech recognition for unsegmented recordings
S Watanabe, M Mandel, J Barker, E Vincent… - ar** for single-and multi-channel speech enhancement and robust ASR
This study proposes a complex spectral map** approach for single-and multi-channel
speech enhancement, where deep neural networks (DNNs) are used to predict the real and …
speech enhancement, where deep neural networks (DNNs) are used to predict the real and …
ESPnet: End-to-end speech processing toolkit
This paper introduces a new open source platform for end-to-end speech processing named
ESPnet. ESPnet mainly focuses on end-to-end automatic speech recognition (ASR), and …
ESPnet. ESPnet mainly focuses on end-to-end automatic speech recognition (ASR), and …