Distant Speech Recognition
10 papers with code • 2 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Distant Speech Recognition
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Libraries
Use these libraries to find Distant Speech Recognition models and implementations
ReVerb Challenge
DIRHA
DiPCo
Latest papers with no code
Direction-Aware Joint Adaptation of Neural Speech Enhancement and Recognition in Real Multiparty Conversational Environments
This paper describes noisy speech recognition for an augmented reality headset that helps verbal communication within real multiparty conversational environments.
Analyzing Large Receptive Field Convolutional Networks for Distant Speech Recognition
In the present study, we address this issue by investigating variants of large receptive field CNNs (LRF-CNNs) which include deeply recursive networks, dilated convolutional neural networks, and stacked hourglass networks.
Frequency Domain Multi-channel Acoustic Modeling for Distant Speech Recognition
Our result also shows that our network with the spatial filtering layer on two-channel input achieves a relative WER reduction of~9. 5\% compared to conventional beamforming with seven microphones.
Multi-Geometry Spatial Acoustic Modeling for Distant Speech Recognition
In contrast to deep clustering methods that treat a neural network as a black box tool, the network encoding the spatial filters can process streaming audio data in real time without the accumulation of target signal statistics.
A Study of Enhancement, Augmentation, and Autoencoder Methods for Domain Adaptation in Distant Speech Recognition
Speech recognizers trained on close-talking speech do not generalize to distant speech and the word error rate degradation can be as large as 40% absolute.
Automatic context window composition for distant speech recognition
Distant speech recognition is being revolutionized by deep learning, that has contributed to significantly outperform previous HMM-GMM systems.
Building state-of-the-art distant speech recognition using the CHiME-4 challenge with a setup of speech enhancement baseline
This paper describes a new baseline system for automatic speech recognition (ASR) in the CHiME-4 challenge to promote the development of noisy ASR in speech processing communities by providing 1) state-of-the-art system with a simplified single system comparable to the complicated top systems in the challenge, 2) publicly available and reproducible recipe through the main repository in the Kaldi speech recognition toolkit.
Deep Learning for Distant Speech Recognition
Deep learning is an emerging technology that is considered one of the most promising directions for reaching higher levels of artificial intelligence.
BridgeNets: Student-Teacher Transfer Learning Based on Recursive Neural Networks and its Application to Distant Speech Recognition
Despite the remarkable progress achieved on automatic speech recognition, recognizing far-field speeches mixed with various noise sources is still a challenging task.
Batch-normalized joint training for DNN-based distant speech recognition
Improving distant speech recognition is a crucial step towards flexible human-machine interfaces.
