7 citations · 12 across the 6 of their papers we have counts for
7 papers
Kernel Support Vector Machine Classifiers with the -Norm Hinge Loss
Rongrong Lin, Yingjia Yao, Yulan Liu
Support Vector Machine (SVM) has been one of the most successful machine learning techniques for binary classification problems. The key idea is to maximize the margin from the dat…
Multi-turn RNN-T for streaming recognition of multi-party speech
Ilya Sklyar, Anna Piunova, Xianrui Zheng +1
Automatic speech recognition (ASR) of single channel far-field recordings with an unknown number of speakers is traditionally tackled by cascaded modules. Recent research shows tha…
SynthASR: Unlocking Synthetic Data for Speech Recognition
Amin Fazel, Wei Yang, Yulan Liu +4
End-to-end (E2E) automatic speech recognition (ASR) models have recently demonstrated superior performance over the traditional hybrid ASR models. Training an E2E ASR model require…
Bootstrap an end-to-end ASR system by multilingual training, transfer learning, text-to-text mapping and synthetic audio
Manuel Giollo, Deniz Gunceler, Yulan Liu +1
Bootstrapping speech recognition on limited data resources has been an area of active research for long. The recent transition to all-neural models and end-to-end (E2E) training br…
Streaming Multi-speaker ASR with RNN-T
Ilya Sklyar, Anna Piunova, Yulan Liu
Recent research shows end-to-end ASR systems can recognize overlapped speech from multiple speakers. However, all published works have assumed no latency constraints during inferen…
Using Synthetic Audio to Improve The Recognition of Out-Of-Vocabulary Words in End-To-End ASR Systems
Xianrui Zheng, Yulan Liu, Deniz Gunceler +1
Today, many state-of-the-art automatic speech recognition (ASR) systems apply all-neural models that map audio to word sequences trained end-to-end along one global optimisation cr…
The 2015 Sheffield System for Transcription of Multi-Genre Broadcast Media
Oscar Saz, Mortaza Doulaty, Salil Deena +5
We describe the University of Sheffield system for participation in the 2015 Multi-Genre Broadcast (MGB) challenge task of transcribing multi-genre broadcast shows. Transcription w…