Search Results for author:
Found 10 papers, 2 papers with code
Efficient Weight factorization for Multilingual Speech Recognition
The key idea of the method is to assign fast weight matrices for each language by decomposing each weight matrix into a shared component and a language dependent component.
Super-Human Performance in Online Low-latency Recognition of Conversational Speech
Achieving super-human performance in recognizing human speech has been a goal for several decades, as researchers have worked on increasingly challenging tasks.
Low Latency ASR for Simultaneous Speech Translation
User studies have shown that reducing the latency of our simultaneous lecture translation system should be the most important goal.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
High Performance Sequence-to-Sequence Model for Streaming Speech Recognition
However, when it comes to performing run-on recognition on an input stream of audio data while producing recognition results in real-time and with low word-based latency, these models face several challenges.
Improving sequence-to-sequence speech recognition training with on-the-fly data augmentation
Sequence-to-Sequence (S2S) models recently started to show state-of-the-art performance for automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Learning Shared Encoding Representation for End-to-End Speech Recognition Models
In this work, we learn a shared encoding representation for a multi-task neural network model optimized with connectionist temporal classification (CTC) and conventional framewise cross-entropy training criteria.
Using multi-task learning to improve the performance of acoustic-to-word and conventional hybrid models
Acoustic-to-word (A2W) models that allow direct mapping from acoustic signals to word sequences are an appealing approach to end-to-end automatic speech recognition due to their simplicity.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the "Speaking Rosetta" JSALT 2017 Workshop
We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and scientific issues surrounding the discovery of linguistic units (subwords and words) in a language without orthography.
