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Found 7 papers, 1 papers with code
Conformer-Based Speech Recognition On Extreme Edge-Computing Devices
With increasingly more powerful compute capabilities and resources in today's devices, traditionally compute-intensive automatic speech recognition (ASR) has been moving from the cloud to devices to better protect user privacy.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Towards Real-World Streaming Speech Translation for Code-Switched Speech
Code-switching (CS), i. e. mixing different languages in a single sentence, is a common phenomenon in communication and can be challenging in many Natural Language Processing (NLP) settings.
Personalization of CTC-based End-to-End Speech Recognition Using Pronunciation-Driven Subword Tokenization
Recent advances in deep learning and automatic speech recognition have improved the accuracy of end-to-end speech recognition systems, but recognition of personal content such as contact names remains a challenge.
Acoustic Model Fusion for End-to-end Speech Recognition
Recent advances in deep learning and automatic speech recognition (ASR) have enabled the end-to-end (E2E) ASR system and boosted the accuracy to a new level.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
A Treatise On FST Lattice Based MMI Training
Maximum mutual information (MMI) has become one of the two de facto methods for sequence-level training of speech recognition acoustic models.
Online Automatic Speech Recognition with Listen, Attend and Spell Model
The Listen, Attend and Spell (LAS) model and other attention-based automatic speech recognition (ASR) models have known limitations when operated in a fully online mode.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
SNDCNN: Self-normalizing deep CNNs with scaled exponential linear units for speech recognition
The most popular way to train very deep CNNs is to use shortcut connections (SC) together with batch normalization (BN).
