8 citations · 10 across the 5 of their papers we have counts for
8 papers
Factorized Neural Transducer for Efficient Language Model Adaptation
Xie Chen, Zhong Meng, Sarangarajan Parthasarathy +1
In recent years, end-to-end (E2E) based automatic speech recognition (ASR) systems have achieved great success due to their simplicity and promising performance. Neural Transducer…
Minimum Word Error Rate Training with Language Model Fusion for End-to-End Speech Recognition
Zhong Meng, Yu Wu, Naoyuki Kanda +6
Integrating external language models (LMs) into end-to-end (E2E) models remains a challenging task for domain-adaptive speech recognition. Recently, internal language model estimat…
Internal Language Model Training for Domain-Adaptive End-to-End Speech Recognition
Zhong Meng, Naoyuki Kanda, Yashesh Gaur +6
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…
Internal Language Model Estimation for Domain-Adaptive End-to-End Speech Recognition
Zhong Meng, Sarangarajan Parthasarathy, Eric Sun +7
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 la…
LSTM-LM with Long-Term History for First-Pass Decoding in Conversational Speech Recognition
Xie Chen, Sarangarajan Parthasarathy, William Gale +2
LSTM language models (LSTM-LMs) have been proven to be powerful and yielded significant performance improvements over count based n-gram LMs in modern speech recognition systems. D…
Developing Real-time Streaming Transformer Transducer for Speech Recognition on Large-scale Dataset
Xie Chen, Yu Wu, Zhenghao Wang +2
Recently, Transformer based end-to-end models have achieved great success in many areas including speech recognition. However, compared to LSTM models, the heavy computational cost…