93 citations · 307 across the 35 of their papers we have counts for
8 papers · 1 filter
Bayes risk CTC: Controllable CTC alignment in Sequence-to-Sequence tasks
Jinchuan Tian, Brian Yan, Jianwei Yu +3
Sequence-to-Sequence (seq2seq) tasks transcribe the input sequence to a target sequence. The Connectionist Temporal Classification (CTC) criterion is widely used in multiple seq2se…
LAE: Language-Aware Encoder for Monolingual and Multilingual ASR
Jinchuan Tian, Jianwei Yu, Chunlei Zhang +3
Despite the rapid progress in automatic speech recognition (ASR) research, recognizing multilingual speech using a unified ASR system remains highly challenging. Previous works on…
Integrating Lattice-Free MMI into End-to-End Speech Recognition
Jinchuan Tian, Jianwei Yu, Chao Weng +2
In automatic speech recognition (ASR) research, discriminative criteria have achieved superior performance in DNN-HMM systems. Given this success, the adoption of discriminative cr…
Improving Mandarin End-to-End Speech Recognition with Word N-gram Language Model
Jinchuan Tian, Jianwei Yu, Chao Weng +2
Despite the rapid progress of end-to-end (E2E) automatic speech recognition (ASR), it has been shown that incorporating external language models (LMs) into the decoding can further…
Mixed Precision of Quantization of Transformer Language Models for Speech Recognition
Junhao Xu, Shoukang Hu, Jianwei Yu +2
State-of-the-art neural language models represented by Transformers are becoming increasingly complex and expensive for practical applications. Low-bit deep neural network quantiza…
Mixed Precision Low-bit Quantization of Neural Network Language Models for Speech Recognition
Junhao Xu, Jianwei Yu, Shoukang Hu +2
State-of-the-art language models (LMs) represented by long-short term memory recurrent neural networks (LSTM-RNNs) and Transformers are becoming increasingly complex and expensive…
ASR-GLUE: A New Multi-task Benchmark for ASR-Robust Natural Language Understanding
Lingyun Feng, Jianwei Yu, Deng Cai +3
Language understanding in speech-based systems have attracted much attention in recent years with the growing demand for voice interface applications. However, the robustness of na…
Bayesian Transformer Language Models for Speech Recognition
Boyang Xue, Jianwei Yu, Junhao Xu +6
State-of-the-art neural language models (LMs) represented by Transformers are highly complex. Their use of fixed, deterministic parameter estimates fail to account for model uncert…