[PDF][PDF] Recent advances in end-to-end automatic speech recognition
J Li - APSIPA Transactions on Signal and Information …, 2022 - nowpublishers.com
Recently, the speech community is seeing a significant trend of moving from deep neural
network based hybrid modeling to end-to-end (E2E) modeling for automatic speech …
network based hybrid modeling to end-to-end (E2E) modeling for automatic speech …
How might we create better benchmarks for speech recognition?
A Aksënova, D van Esch, J Flynn… - Proceedings of the 1st …, 2021 - aclanthology.org
The applications of automatic speech recognition (ASR) systems are proliferating, in part
due to recent significant quality improvements. However, as recent work indicates, even …
due to recent significant quality improvements. However, as recent work indicates, even …
Zeroprompt: streaming acoustic encoders are zero-shot masked lms
In this paper, we present ZeroPrompt (Figure 1-(a)) and the corresponding Prompt-and-
Refine strategy (Figure 3), two simple but effective\textbf {training-free} methods to decrease …
Refine strategy (Figure 3), two simple but effective\textbf {training-free} methods to decrease …
Extreme encoder output frame rate reduction: Improving computational latencies of large end-to-end models
The accuracy of end-to-end (E2E) automatic speech recognition (ASR) models continues to
improve as they are scaled to larger sizes, with some now reaching billions of parameters …
improve as they are scaled to larger sizes, with some now reaching billions of parameters …
The timing bottleneck: Why timing and overlap are mission-critical for conversational user interfaces, speech recognition and dialogue systems
Speech recognition systems are a key intermediary in voice-driven human-computer
interaction. Although speech recognition works well for pristine monologic audio, real-life …
interaction. Although speech recognition works well for pristine monologic audio, real-life …
A CIF-based speech segmentation method for streaming E2E ASR
Long utterances segmentation is crucial in end-to-end (E2E) streaming automatic speech
recognition (ASR). However, commonly used voice activity detection (VAD)-based and fixed …
recognition (ASR). However, commonly used voice activity detection (VAD)-based and fixed …
Unified end-to-end speech recognition and endpointing for fast and efficient speech systems
Automatic speech recognition (ASR) systems typically rely on an external endpointer (EP)
model to identify speech boundaries. In this work, we propose a method to jointly train the …
model to identify speech boundaries. In this work, we propose a method to jointly train the …
Fast-u2++: Fast and accurate end-to-end speech recognition in joint ctc/attention frames
Recently, the unified streaming and non-streaming two-pass (U2/U2++) end-to-end model
for speech recognition has shown great performance in terms of streaming capability …
for speech recognition has shown great performance in terms of streaming capability …
E2e segmentation in a two-pass cascaded encoder asr model
We explore unifying a neural segmenter with two-pass cascaded encoder ASR into a single
model. A key challenge is allowing the segmenter (which runs in real-time, synchronously …
model. A key challenge is allowing the segmenter (which runs in real-time, synchronously …
Alignment knowledge distillation for online streaming attention-based speech recognition
H Inaguma, T Kawahara - IEEE/ACM Transactions on Audio …, 2021 - ieeexplore.ieee.org
This article describes an efficient training method for online streaming attention-based
encoder-decoder (AED) automatic speech recognition (ASR) systems. AED models have …
encoder-decoder (AED) automatic speech recognition (ASR) systems. AED models have …