34 citations · 177 across the 55 of their papers we have counts for
5 papers · 2 filters
Random Utterance Concatenation Based Data Augmentation for Improving Short-video Speech Recognition
Yist Y. Lin, Tao Han, Haihua Xu +6
One of limitations in end-to-end automatic speech recognition (ASR) framework is its performance would be compromised if train-test utterance lengths are mismatched. In this paper,…
Language Adaptive Cross-lingual Speech Representation Learning with Sparse Sharing Sub-networks
Yizhou Lu, Mingkun Huang, Xinghua Qu +2
Unsupervised cross-lingual speech representation learning (XLSR) has recently shown promising results in speech recognition by leveraging vast amounts of unlabeled data across mult…
Improving Non-native Word-level Pronunciation Scoring with Phone-level Mixup Data Augmentation and Multi-source Information
Kaiqi Fu, Shaojun Gao, Kai Wang +3
Deep learning-based pronunciation scoring models highly rely on the availability of the annotated non-native data, which is costly and has scalability issues. To deal with the data…
S3T: Self-Supervised Pre-training with Swin Transformer for Music Classification
Hang Zhao, Chen Zhang, Belei Zhu +2
In this paper, we propose S3T, a self-supervised pre-training method with Swin Transformer for music classification, aiming to learn meaningful music representations from massive e…
Internal Language Model Estimation Through Explicit Context Vector Learning for Attention-based Encoder-decoder ASR
Yufei Liu, Rao Ma, Haihua Xu +3
An end-to-end (E2E) ASR model implicitly learns a prior Internal Language Model (ILM) from the training transcripts. To fuse an external LM using Bayes posterior theory, the log li…