Distant Speech Recognition
10 papers with code • 2 benchmarks • 3 datasets
Libraries
Use these libraries to find Distant Speech Recognition models and implementationsMost implemented papers
The PyTorch-Kaldi Speech Recognition Toolkit
Experiments, that are conducted on several datasets and tasks, show that PyTorch-Kaldi can effectively be used to develop modern state-of-the-art speech recognizers.
Residual LSTM: Design of a Deep Recurrent Architecture for Distant Speech Recognition
The residual LSTM provides an additional spatial shortcut path from lower layers for efficient training of deep networks with multiple LSTM layers.
The DIRHA-English corpus and related tasks for distant-speech recognition in domestic environments
This paper introduces the contents and the possible usage of the DIRHA-ENGLISH multi-microphone corpus, recently realized under the EC DIRHA project.
MeshRIR: A Dataset of Room Impulse Responses on Meshed Grid Points For Evaluating Sound Field Analysis and Synthesis Methods
Two subdatasets are currently available: one consists of IRs in a three-dimensional cuboidal region from a single source, and the other consists of IRs in a two-dimensional square region from an array of 32 sources.
Open Source German Distant Speech Recognition: Corpus and Acoustic Model
We present a new freely available corpus for German distant speech recognition and report speaker-independent word error rate (WER) results for two open source speech recognizers trained on this corpus.
Contaminated speech training methods for robust DNN-HMM distant speech recognition
Despite the significant progress made in the last years, state-of-the-art speech recognition technologies provide a satisfactory performance only in the close-talking condition.
Interpretable Convolutional Filters with SincNet
Deep learning is currently playing a crucial role toward higher levels of artificial intelligence.
Learning Problem-agnostic Speech Representations from Multiple Self-supervised Tasks
Learning good representations without supervision is still an open issue in machine learning, and is particularly challenging for speech signals, which are often characterized by long sequences with a complex hierarchical structure.
Quaternion Neural Networks for Multi-channel Distant Speech Recognition
In this paper, we propose to capture these inter- and intra- structural dependencies with quaternion neural networks, which can jointly process multiple signals as whole quaternion entities.
Learning to Rank Microphones for Distant Speech Recognition
Fully exploiting ad-hoc microphone networks for distant speech recognition is still an open issue.