9 citations · 16 across the 9 of their papers we have counts for
5 papers · 1 filter
Speaker Adaptive Training using Model Agnostic Meta-Learning
Ondřej Klejch, Joachim Fainberg, Peter Bell +1
Speaker adaptive training (SAT) of neural network acoustic models learns models in a way that makes them more suitable for adaptation to test conditions. Conventionally, model-base…
Acoustic Model Adaptation from Raw Waveforms with SincNet
Joachim Fainberg, Ondřej Klejch, Erfan Loweimi +2
Raw waveform acoustic modelling has recently gained interest due to neural networks' ability to learn feature extraction, and the potential for finding better representations for a…
Lattice-Based Unsupervised Test-Time Adaptation of Neural Network Acoustic Models
Ondrej Klejch, Joachim Fainberg, Peter Bell +1
Acoustic model adaptation to unseen test recordings aims to reduce the mismatch between training and testing conditions. Most adaptation schemes for neural network models require t…
Lattice-based lightly-supervised acoustic model training
Joachim Fainberg, Ondřej Klejch, Steve Renals +1
In the broadcast domain there is an abundance of related text data and partial transcriptions, such as closed captions and subtitles. This text data can be used for lightly supervi…
AVA-ActiveSpeaker: An Audio-Visual Dataset for Active Speaker Detection
Joseph Roth, Sourish Chaudhuri, Ondrej Klejch +8
Active speaker detection is an important component in video analysis algorithms for applications such as speaker diarization, video re-targeting for meetings, speech enhancement, a…