20 citations · 53 across the 5 of their papers we have counts for
5 papers
Leveraging Text Data Using Hybrid Transformer-LSTM Based End-to-End ASR in Transfer Learning
Zhiping Zeng, Van Tung Pham, Haihua Xu +4
In this work, we study leveraging extra text data to improve low-resource end-to-end ASR under cross-lingual transfer learning setting. To this end, we extend our prior work [1], a…
Independent language modeling architecture for end-to-end ASR
Van Tung Pham, Haihua Xu, Yerbolat Khassanov +5
The attention-based end-to-end (E2E) automatic speech recognition (ASR) architecture allows for joint optimization of acoustic and language models within a single network. However,…
Constrained Output Embeddings for End-to-End Code-Switching Speech Recognition with Only Monolingual Data
Yerbolat Khassanov, Haihua Xu, Van Tung Pham +4
The lack of code-switch training data is one of the major concerns in the development of end-to-end code-switching automatic speech recognition (ASR) models. In this work, we propo…
Enriching Rare Word Representations in Neural Language Models by Embedding Matrix Augmentation
Yerbolat Khassanov, Zhiping Zeng, Van Tung Pham +2
The neural language models (NLM) achieve strong generalization capability by learning the dense representation of words and using them to estimate probability distribution function…
On the End-to-End Solution to Mandarin-English Code-switching Speech Recognition
Zhiping Zeng, Yerbolat Khassanov, Van Tung Pham +3
Code-switching (CS) refers to a linguistic phenomenon where a speaker uses different languages in an utterance or between alternating utterances. In this work, we study end-to-end…