no code implementations • 26 May 2023 • Michael Levit, Sarangarajan Parthasarathy, Cem Aksoylar, Mohammad Sadegh Rasooli, Shuangyu Chang
We propose an adaptation method for factorized neural transducers (FNT) with external language models.
no code implementations • 8 Sep 2022 • Li Miao, Jian Wu, Piyush Behre, Shuangyu Chang, Sarangarajan Parthasarathy
It is challenging to train and deploy Transformer LMs for hybrid speech recognition 2nd pass re-ranking in low-resource languages due to (1) data scarcity in low-resource languages, (2) expensive computing costs for training and refreshing 100+ monolingual models, and (3) hosting inefficiency considering sparse traffic.
1 code implementation • 27 Sep 2021 • Xie Chen, Zhong Meng, Sarangarajan Parthasarathy, Jinyu Li
In recent years, end-to-end (E2E) based automatic speech recognition (ASR) systems have achieved great success due to their simplicity and promising performance.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 2 Feb 2021 • Zhong Meng, Naoyuki Kanda, Yashesh Gaur, Sarangarajan Parthasarathy, Eric Sun, Liang Lu, Xie Chen, Jinyu Li, Yifan Gong
The efficacy of external language model (LM) integration with existing end-to-end (E2E) automatic speech recognition (ASR) systems can be improved significantly using the internal language model estimation (ILME) method.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 3 Nov 2020 • Zhong Meng, Sarangarajan Parthasarathy, Eric Sun, Yashesh Gaur, Naoyuki Kanda, Liang Lu, Xie Chen, Rui Zhao, Jinyu Li, Yifan Gong
The external language models (LM) integration remains a challenging task for end-to-end (E2E) automatic speech recognition (ASR) which has no clear division between acoustic and language models.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 21 Oct 2020 • Xie Chen, Sarangarajan Parthasarathy, William Gale, Shuangyu Chang, Michael Zeng
The context information is captured by the hidden states of LSTM-LMs across utterance and can be used to guide the first-pass search effectively.
no code implementations • 30 Jul 2020 • Jinyu Li, Rui Zhao, Zhong Meng, Yanqing Liu, Wenning Wei, Sarangarajan Parthasarathy, Vadim Mazalov, Zhenghao Wang, Lei He, Sheng Zhao, Yifan Gong
Because of its streaming nature, recurrent neural network transducer (RNN-T) is a very promising end-to-end (E2E) model that may replace the popular hybrid model for automatic speech recognition.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 11 Nov 2019 • Sarangarajan Parthasarathy, William Gale, Xie Chen, George Polovets, Shuangyu Chang
We conduct language modeling and speech recognition experiments on the publicly available LibriSpeech corpus.
no code implementations • 12 Mar 2018 • Mohammad Sadegh Rasooli, Sarangarajan Parthasarathy
One solution is to use a reranker trained with global features, in which global features are derived from n-best lists.