Lyan Verwimp

发表

Extending n-gram language models based on syntactic equivalences

Lyan Verwimp, Joris Pelemans, Hugo Van hamme, 2015 .

Addressing Limitations of Language Models

Lyan Verwimp, 2019 .

Project STON: speeding up Dutch subtitling with speech and language technology

Lyan Verwimp, Joris Pelemans, Patrick Wambacq, 2017 .

SCATE – Smart Computer-Aided Translation Environment – Year 3 (/4)

Lyan Verwimp, Joris Pelemans, Patrick Wambacq, 2017 .

Language Models of Spoken Dutch pdf

Lyan Verwimp, Joris Pelemans, Hugo Van hamme, 2017, ArXiv.

STON: Efficient Subtitling in Dutch Using State-of-the-Art Tools

Lyan Verwimp, Joris Pelemans, Patrick Wambacq, 2016, INTERSPEECH.

Extending n-gram language models based on equivalent syntactic patterns

Lyan Verwimp, Joris Pelemans, Hugo Van hamme, 2015 .

Improving the Translation Environment for Professional Translators

Lyan Verwimp, Joris Pelemans, Patrick Wambacq, 2019, Informatics.

Character-Word LSTM Language Models

Lyan Verwimp, Joris Pelemans, Hugo Van hamme, 2017, EACL.

Pictograph-to-Text Translation for Augmented and Alternative Communication

Lyan Verwimp, Patrick Wambacq, Frank Van Eynde, 2018 .

State Gradients for RNN Memory Analysis pdf

Lyan Verwimp, Hugo Van hamme, Patrick Wambacq, 2018, INTERSPEECH.

Language model adaptation for ASR of spoken translations using phrase-based translation models and named entity models

Lyan Verwimp, Joris Pelemans, Hugo Van hamme, 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Reverse Transfer Learning: Can Word Embeddings Trained for Different NLP Tasks Improve Neural Language Models? pdf

Lyan Verwimp, Jerome R. Bellegarda, J. Bellegarda, 2019, INTERSPEECH.

Information-Weighted Neural Cache Language Models for ASR

Lyan Verwimp, Joris Pelemans, Hugo Van hamme, 2018, 2018 IEEE Spoken Language Technology Workshop (SLT).

Augmenting recurrent neural network language models with subword information

Lyan Verwimp, Joris Pelemans, Hugo Van hamme, 2015 .

State Gradients for RNN Memory Analysis

Lyan Verwimp, Patrick Wambacq, Hugo Van hamme, 2018, EMNLP 2018.

Expanding n-gram training data for language models based on morpho-syntactic transformations

Lyan Verwimp, Joris Pelemans, Patrick Wambacq, 2015 .

State gradients for analyzing memory in LSTM language models

Lyan Verwimp, Hugo Van hamme, Patrick Wambacq, 2020, Comput. Speech Lang..

Machine translation-based language model adaptation for automatic speech recognition of spoken translations

Lyan Verwimp, Joris Pelemans, Hugo Van hamme, 2015 .

On the long-term learning ability of LSTM LMs

Lyan Verwimp, Joris Pelemans, Patrick Wambacq, 2020, ESANN.

Smart Computer-Aided Translation Environment (SCATE): Highlights

Lyan Verwimp, Joris Pelemans, Patrick Wambacq, 2018 .

Analyzing the Contribution of Top-Down Lexical and Bottom-Up Acoustic Cues in the Detection of Sentence Prominence

Lyan Verwimp, Joris Pelemans, Patrick Wambacq, 2016, INTERSPEECH.

SCALE: A Scalable Language Engineering Toolkit

Lyan Verwimp, Joris Pelemans, Hugo Van hamme, 2016, LREC.

145 ways to insert punctuation for speech translation

Lyan Verwimp, Joris Pelemans, Patrick Wambacq, 2018 .

A Comparison of Different Punctuation Prediction Approaches in a Translation Context

Lyan Verwimp, Joris Pelemans, Patrick Wambacq, 2018, EAMT.

Domain adaptation for LSTM language models

Lyan Verwimp, Joris Pelemans, Patrick Wambacq, 2017 .

TF-LM: TensorFlow-based Language Modeling Toolkit

Lyan Verwimp, Hugo Van hamme, Patrick Wambacq, 2018, LREC.

Error-Driven Pruning of Language Models for Virtual Assistants

Lyan Verwimp, Manos Tsagkias, Ernest Pusateri, 2021, ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).