[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 …
Scaling speech technology to 1,000+ languages
Expanding the language coverage of speech technology has the potential to improve
access to information for many more people. However, current speech technology is …
access to information for many more people. However, current speech technology is …
Robust speech recognition via large-scale weak supervision
We study the capabilities of speech processing systems trained simply to predict large
amounts of transcripts of audio on the internet. When scaled to 680,000 hours of multilingual …
amounts of transcripts of audio on the internet. When scaled to 680,000 hours of multilingual …
XLS-R: Self-supervised cross-lingual speech representation learning at scale
This paper presents XLS-R, a large-scale model for cross-lingual speech representation
learning based on wav2vec 2.0. We train models with up to 2B parameters on nearly half a …
learning based on wav2vec 2.0. We train models with up to 2B parameters on nearly half a …
Emerging trends: A gentle introduction to fine-tuning
The previous Emerging Trends article (Church et al., 2021. Natural Language
Engineering27 (5), 631–645.) introduced deep nets to poets. Poets is an imperfect …
Engineering27 (5), 631–645.) introduced deep nets to poets. Poets is an imperfect …
Branchformer: Parallel mlp-attention architectures to capture local and global context for speech recognition and understanding
Conformer has proven to be effective in many speech processing tasks. It combines the
benefits of extracting local dependencies using convolutions and global dependencies …
benefits of extracting local dependencies using convolutions and global dependencies …
Layer-wise analysis of a self-supervised speech representation model
Recently proposed self-supervised learning approaches have been successful for pre-
training speech representation models. The utility of these learned representations has been …
training speech representation models. The utility of these learned representations has been …
Torchaudio: Building blocks for audio and speech processing
This document describes version 0.10 of TorchAudio: building blocks for machine learning
applications in the audio and speech processing domain. The objective of TorchAudio is to …
applications in the audio and speech processing domain. The objective of TorchAudio is to …
Transformer-based multimodal information fusion for facial expression analysis
Human affective behavior analysis has received much attention in human-computer
interaction (HCI). In this paper, we introduce our submission to the CVPR 2022 Competition …
interaction (HCI). In this paper, we introduce our submission to the CVPR 2022 Competition …
Speech emotion recognition using self-supervised features
Self-supervised pre-trained features have consistently delivered state-of-art results in the
field of natural language processing (NLP); however, their merits in the field of speech …
field of natural language processing (NLP); however, their merits in the field of speech …