7 citations · 13 across the 7 of their papers we have counts for
7 papers
Synthetic Cross-accent Data Augmentation for Automatic Speech Recognition
Philipp Klumpp, Pooja Chitkara, Leda Sarı +5
The awareness for biased ASR datasets or models has increased notably in recent years. Even for English, despite a vast amount of available training data, systems perform worse for…
Joint Audio/Text Training for Transformer Rescorer of Streaming Speech Recognition
Suyoun Kim, Ke Li, Lucas Kabela +4
Recently, there has been an increasing interest in two-pass streaming end-to-end speech recognition (ASR) that incorporates a 2nd-pass rescoring model on top of the conventional 1s…
Named Entity Detection and Injection for Direct Speech Translation
Marco Gaido, Yun Tang, Ilia Kulikov +3
In a sentence, certain words are critical for its semantic. Among them, named entities (NEs) are notoriously challenging for neural models. Despite their importance, their accurate…
Integrating Categorical Features in End-to-End ASR
Rongqing Huang
All-neural, end-to-end ASR systems gained rapid interest from the speech recognition community. Such systems convert speech input to text units using a single trainable neural netw…
Class LM and word mapping for contextual biasing in End-to-End ASR
Rongqing Huang, Ossama Abdel-hamid, Xinwei Li +1
In recent years, all-neural, end-to-end (E2E) ASR systems gained rapid interest in the speech recognition community. They convert speech input to text units in a single trainable N…
Network-Scale Traffic Modeling and Forecasting with Graphical Lasso and Neural Networks
Shiliang Sun, Rongqing Huang, Ya Gao
Traffic flow forecasting, especially the short-term case, is an important topic in intelligent transportation systems (ITS). This paper does a lot of research on network-scale mode…
Kernel Regression with Sparse Metric Learning
Rongqing Huang, Shiliang Sun
Kernel regression is a popular non-parametric fitting technique. It aims at learning a function which estimates the targets for test inputs as precise as possible. Generally, the f…