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Found 5 papers, 0 papers with code
Two-Stage Augmentation and Adaptive CTC Fusion for Improved Robustness of Multi-Stream End-to-End ASR
Performance degradation of an Automatic Speech Recognition (ASR) system is commonly observed when the test acoustic condition is different from training.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
A practical two-stage training strategy for multi-stream end-to-end speech recognition
The multi-stream paradigm of audio processing, in which several sources are simultaneously considered, has been an active research area for information fusion.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Performance Monitoring for End-to-End Speech Recognition
Measuring performance of an automatic speech recognition (ASR) system without ground-truth could be beneficial in many scenarios, especially with data from unseen domains, where performance can be highly inconsistent.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Building Corpora for Single-Channel Speech Separation Across Multiple Domains
To date, the bulk of research on single-channel speech separation has been conducted using clean, near-field, read speech, which is not representative of many modern applications.
Scalable Out-of-Sample Extension of Graph Embeddings Using Deep Neural Networks
Several popular graph embedding techniques for representation learning and dimensionality reduction rely on performing computationally expensive eigendecompositions to derive a nonlinear transformation of the input data space.
