Beáta Lorincz

Publication Activity (10 Years)

Years Active: 2019-2023
Publications (10 Years): 14

Top Topics

Objective Evaluation

Automatically Extracted

Top Venues

Nat. Lang. Eng.

Publications

Beáta Lorincz, Elena Irimia, Adriana Stan, Verginica Barbu Mititelu
RoLEX: The development of an extended Romanian lexical dataset and its evaluation at predicting concurrent lexical information. Nat. Lang. Eng. 29 (3) (2023)
Dan Oneata, Beáta Lorincz, Adriana Stan, Horia Cucu
FlexLip: A Controllable Text-to-Lip System. CoRR (2022)
Dan Oneata, Beáta Lorincz, Adriana Stan, Horia Cucu
FlexLip: A Controllable Text-to-Lip System. Sensors 22 (11) (2022)
Beáta Lorincz, Adriana Stan, Mircea Giurgiu
An objective evaluation of the effects of recording conditions and speaker characteristics in multi-speaker deep neural speech synthesis. KES (2021)
Adriana Stan, Beáta Lorincz, Maria Nutu, Mircea Giurgiu
The MARA corpus: Expressivity in end-to-end TTS systems using synthesised speech data. SpeD (2021)
Beáta Lorincz, Adriana Stan, Mircea Giurgiu
Speaker verification-derived loss and data augmentation for DNN-based multispeaker speech synthesis. CoRR (2021)
Stefan Daniel Dumitrescu, Petru Rebeja, Beáta Lorincz, Mihaela Gaman, Andrei-Marius Avram, Mihai Ilie, Andrei Pruteanu, Adriana Stan, Lorena Rosia, Cristina Iacobescu, Luciana Morogan, George Dima, Gabriel Marchidan, Traian Rebedea, Madalina Chitez, Dani Yogatama, Sebastian Ruder, Radu Tudor Ionescu, Razvan Pascanu, Viorica Patraucean
LiRo: Benchmark and leaderboard for Romanian language tasks. NeurIPS Datasets and Benchmarks (2021)
Beáta Lorincz, Bogdan Iudean, Andreea Vescan
Experience report on teaching testing through gamification. EASEAI@ESEC/SIGSOFT FSE (2021)
Beáta Lorincz, Adriana Stan, Mircea Giurgiu
An objective evaluation of the effects of recording conditions and speaker characteristics in multi-speaker deep neural speech synthesis. CoRR (2021)
Beáta Lorincz, Adriana Stan, Mircea Giurgiu
Speaker verification-derived loss and data augmentation for DNN-based multispeaker speech synthesis. EUSIPCO (2021)
Beáta Lorincz
Concurrent phonetic transcription, lexical stress assignment and syllabification with deep neural networks. KES (2020)
Beáta Lorincz, Maria Nutu, Adriana Stan, Mircea Giurgiu
An Evaluation of Postfiltering for Deep Learning Based Speech Synthesis with Limited Data. IEEE Conf. on Intelligent Systems (2020)
Beáta Lorincz, Maria Nutu, Adriana Stan
Romanian Part of Speech Tagging using LSTM Networks. ICCP (2019)
Maria Nutu, Beáta Lorincz, Adriana Stan
Deep Learning for Automatic Diacritics Restoration in Romanian. ICCP (2019)