23 citations · 43 across the 11 of their papers we have counts for
5 papers · 1 filter
Reducing Language confusion for Code-switching Speech Recognition with Token-level Language Diarization
Hexin Liu, Haihua Xu, Leibny Paola Garcia +3
Code-switching (CS) refers to the phenomenon that languages switch within a speech signal and leads to language confusion for automatic speech recognition (ASR). This paper aims to…
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,…
Intermediate-layer output Regularization for Attention-based Speech Recognition with Shared Decoder
Jicheng Zhang, Yizhou Peng, Haihua Xu +3
Intermediate layer output (ILO) regularization by means of multitask training on encoder side has been shown to be an effective approach to yielding improved results on a wide rang…
Internal Language Model Estimation based Language Model Fusion for Cross-Domain Code-Switching Speech Recognition
Yizhou Peng, Yufei Liu, Jicheng Zhang +4
Internal Language Model Estimation (ILME) based language model (LM) fusion has been shown significantly improved recognition results over conventional shallow fusion in both intra-…
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…