Robust Speech Recognition
22 papers with code • 0 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Robust Speech Recognition
DiPCo
Google Speech Commands - Musan
FSC-P2
Latest papers with no code
Multiple Confidence Gates For Joint Training Of SE And ASR
Joint training of speech enhancement model (SE) and speech recognition model (ASR) is a common solution for robust ASR in noisy environments.
Noise-robust Speech Recognition with 10 Minutes Unparalleled In-domain Data
Noise-robust speech recognition systems require large amounts of training data including noisy speech data and corresponding transcripts to achieve state-of-the-art performances in face of various practical environments.
Chain-based Discriminative Autoencoders for Speech Recognition
For application to robust speech recognition, we further extend c-DcAE to hierarchical and parallel structures, resulting in hc-DcAE and pc-DcAE.
Investigation of Densely Connected Convolutional Networks with Domain Adversarial Learning for Noise Robust Speech Recognition
We investigate densely connected convolutional networks (DenseNets) and their extension with domain adversarial training for noise robust speech recognition.
A comparison of streaming models and data augmentation methods for robust speech recognition
However, we observe that training of MoChA models seems to be more sensitive to various factors such as the characteristics of training sets and the incorporation of additional augmentations techniques.
Wav2vec-Switch: Contrastive Learning from Original-noisy Speech Pairs for Robust Speech Recognition
In this paper we propose wav2vec-Switch, a method to encode noise robustness into contextualized representations of speech via contrastive learning.
Optimized Power Normalized Cepstral Coefficients towards Robust Deep Speaker Verification
After their introduction to robust speech recognition, power normalized cepstral coefficient (PNCC) features were successfully adopted to other tasks, including speaker verification.
HMM-based phoneme speech recognition system for the control and command of industrial robots
In this study, we aim at developing a stable and robust speech recognition system to allow humans to communicate with machines (robotic arms) in a seamless manner.
Aphasic Speech Recognition using a Mixture of Speech Intelligibility Experts
Robust speech recognition is a key prerequisite for semantic feature extraction in automatic aphasic speech analysis.
Deep Learning Based Dereverberation of Temporal Envelopesfor Robust Speech Recognition
Automatic speech recognition in reverberant conditions is a challenging task as the long-term envelopes of the reverberant speech are temporally smeared.
