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ORCIDAdriana Cornelia Stan
Person information
- affiliation: Technical University of Cluj-Napoca, Romania
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2020 – today
- 2023
[j4]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): 720-745 (2023)- [c34]Samuel Rutunda, Kleber Kabanda, Adriana Stan:
Kinyarwanda TTS: Using a multi-speaker dataset to build a Kinyarwanda TTS model. AfricaNLP 2023 - [c33]Adrian Bogdan Stânea, Vlad Striletchi, Cosmin Striletchi, Adriana Cornelia Stan:
An analysis of large speech models-based representations for speech emotion recognition. SpeD 2023: 100-104 - [i9]Adriana Stan:
Residual Information in Deep Speaker Embedding Architectures. CoRR abs/2302.02742 (2023) - [i8]Adriana Stan, Johannah O'Mahony:
An analysis on the effects of speaker embedding choice in non auto-regressive TTS. CoRR abs/2307.09898 (2023) - [i7]Dan Oneata, Adriana Stan, Octavian Pascu, Elisabeta Oneata, Horia Cucu:
Towards generalisable and calibrated synthetic speech detection with self-supervised representations. CoRR abs/2309.05384 (2023) - 2022
- [j3]Dan Oneata, Beáta Lorincz, Adriana Stan, Horia Cucu:
FlexLip: A Controllable Text-to-Lip System. Sensors 22(11): 4104 (2022) - [c32]Adriana Stan:
The ZevoMOS entry to VoiceMOS Challenge 2022. INTERSPEECH 2022: 4516-4520 - [c31]Cosmin Striletchi, Adriana Cornelia Stan, Eusebiu Jecan:
Gamification-Based Tools Embedded in the Helios Educational Platform. WorldCIST (2) 2022: 483-491 - [i6]Dan Oneata, Beáta Lorincz, Adriana Stan, Horia Cucu:
FlexLip: A Controllable Text-to-Lip System. CoRR abs/2206.03206 (2022) - 2021
- [c30]Beáta Lorincz, Adriana Stan, Mircea Giurgiu:
Speaker verification-derived loss and data augmentation for DNN-based multispeaker speech synthesis. EUSIPCO 2021: 26-30 - [c29]Dan Oneata, Adriana Stan, Horia Cucu:
Speaker disentanglement in video-to-speech conversion. EUSIPCO 2021: 46-50 - [c28]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: 756-765 - [c27]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 - [c26]Dan Oneata, Alexandru Caranica, Adriana Stan, Horia Cucu:
An Evaluation of Word-Level Confidence Estimation for End-to-End Automatic Speech Recognition. SLT 2021: 258-265 - [c25]Adriana Stan, Beáta Lorincz, Maria Nutu, Mircea Giurgiu:
The MARA corpus: Expressivity in end-to-end TTS systems using synthesised speech data. SpeD 2021: 85-90 - [c24]Georgiana Saracu, Adriana Stan:
An analysis of the data efficiency in Tacotron2 speech synthesis system. SpeD 2021: 172-176 - [i5]Dan Oneata, Alexandru Caranica, Adriana Stan, Horia Cucu:
An evaluation of word-level confidence estimation for end-to-end automatic speech recognition. CoRR abs/2101.05525 (2021) - [i4]Dan Oneata, Adriana Stan, Horia Cucu:
Speaker disentanglement in video-to-speech conversion. CoRR abs/2105.09652 (2021) - [i3]Beáta Lorincz, Adriana Stan, Mircea Giurgiu:
Speaker verification-derived loss and data augmentation for DNN-based multispeaker speech synthesis. CoRR abs/2106.01789 (2021) - [i2]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 abs/2106.01812 (2021) - 2020
- [c23]Adriana Stan:
RECOApy: Data Recording, Pre-Processing and Phonetic Transcription for End-to-End Speech-Based Applications. INTERSPEECH 2020: 586-590 - [c22]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: 437-442 - [c21]Kristen M. Scott, Simone Ashby, Adriana Stan:
Designing a Synthesized Content Feed System for Community Radio. NordiCHI 2020: 28:1-28:4 - [i1]Adriana Stan:
RECOApy: Data recording, pre-processing and phonetic transcription for end-to-end speech-based applications. CoRR abs/2009.05493 (2020)
2010 – 2019
- 2019
- [c20]Beáta Lorincz, Maria Nutu, Adriana Stan:
Romanian Part of Speech Tagging using LSTM Networks. ICCP 2019: 223-228 - [c19]Maria Nutu, Beáta Lorincz, Adriana Stan:
Deep Learning for Automatic Diacritics Restoration in Romanian. ICCP 2019: 235-240 - [c18]David A. Braude, Matthew P. Aylett, Caoimhín Laoide-Kemp, Simone Ashby, Kristen M. Scott, Brian Ó Raghallaigh, Anna Braudo, Alex Brouwer, Adriana Stan:
All Together Now: The Living Audio Dataset. INTERSPEECH 2019: 1521-1525 - [c17]Adriana Stan:
Input Encoding for Sequence-to-Sequence Learning of Romanian Grapheme-to-Phoneme Conversion. SpeD 2019: 1-6 - 2017
- [c16]Adriana Stan, Florina Dinescu, Cristina Tiple, Serban Meza, Bogdan Orza, Magdalena Chirila, Mircea Giurgiu:
The SWARA speech corpus: A large parallel Romanian read speech dataset. SpeD 2017: 1-6 - [c15]Stefan Adrian Toma, Adriana Stan, Mihai-Lica Pura, Traian Barsan:
MaRePhoR - An open access machine-readable phonetic dictionary for Romanian. SpeD 2017: 1-6 - 2016
- [j2]Adriana Stan, Yoshitaka Mamiya, Junichi Yamagishi, Peter Bell, Oliver Watts, Robert A. J. Clark, Simon King:
ALISA: An automatic lightly supervised speech segmentation and alignment tool. Comput. Speech Lang. 35: 116-133 (2016) - [c14]Alexandru Moldovan, Adriana Stan, Mircea Giurgiu:
Improving sentence-level alignment of speech with imperfect transcripts using utterance concatenation and VAD. ICCP 2016: 171-174 - [c13]Adriana Stan, Cassia Valentini-Botinhao, Bogdan Orza, Mircea Giurgiu:
Blind speech segmentation using spectrogram image-based features and Mel cepstral coefficients. SLT 2016: 597-602 - 2015
- [c12]Adriana Stan, Cassia Valentini-Botinhao, Mircea Giurgiu, Simon King:
Phonetic segmentation of speech using STEP and t-SNE. SpeD 2015: 1-6 - 2014
- [c11]Oliver Watts, Siva Reddy Gangireddy, Junichi Yamagishi, Simon King, Steve Renals, Adriana Stan, Mircea Giurgiu:
Neural net word representations for phrase-break prediction without a part of speech tagger. ICASSP 2014: 2599-2603 - [c10]Tiberiu Boros, Adriana Stan, Oliver Watts, Stefan Daniel Dumitrescu:
RSS-TOBI - A Prosodically Enhanced Romanian Speech Corpus. LREC 2014: 316-320 - 2013
- [c9]Yoshitaka Mamiya, Junichi Yamagishi, Oliver Watts, Robert A. J. Clark, Simon King, Adriana Stan:
Lightly supervised GMM VAD to use audiobook for speech synthesiser. ICASSP 2013: 7987-7991 - [c8]Adriana Stan, Peter Bell, Junichi Yamagishi, Simon King:
Lightly supervised discriminative training of grapheme models for improved sentence-level alignment of speech and text data. INTERSPEECH 2013: 1525-1529 - [c7]Adriana Stan, Oliver Watts, Yoshitaka Mamiya, Mircea Giurgiu, Robert A. J. Clark, Junichi Yamagishi, Simon King:
TUNDRA: a multilingual corpus of found data for TTS research created with light supervision. INTERSPEECH 2013: 2331-2335 - [c6]Ioana Muresan, Adriana Stan, Mircea Giurgiu, Rodica Potolea:
Evaluation of sentiment polarity prediction using a dimensional and a categorical approach. SpeD 2013: 1-6 - [c5]Yoshitaka Mamiya, Adriana Stan, Junichi Yamagishi, Peter Bell, Oliver Watts, Robert A. J. Clark, Simon King:
Using adaptation to improve speech transcription alignment in noisy and reverberant environments. SSW 2013: 41-46 - [c4]Oliver Watts, Adriana Stan, Robert A. J. Clark, Yoshitaka Mamiya, Mircea Giurgiu, Junichi Yamagishi, Simon King:
Unsupervised and lightly-supervised learning for rapid construction of TTS systems in multiple languages from 'found' data: evaluation and analysis. SSW 2013: 101-106 - 2012
- [c3]Adriana Stan, Peter Bell, Simon King:
A grapheme-based method for automatic alignment of speech and text data. SLT 2012: 286-290 - 2011
- [j1]Adriana Stan, Junichi Yamagishi, Simon King, Matthew P. Aylett:
The Romanian speech synthesis (RSS) corpus: Building a high quality HMM-based speech synthesis system using a high sampling rate. Speech Commun. 53(3): 442-450 (2011) - [c2]Adriana Stan, Florin-Claudiu Pop, Marcel Cremene, Mircea Giurgiu, Denis Pallez:
Interactive Intonation Optimisation Using CMA-ES and DCT Parameterisation of the F0 Contour for Speech Synthesis. NICSO 2011: 57-71 - [c1]Adriana Stan, Mircea Giurgiu:
A superpositional model applied to F0 parameterization using DCT for text-to-speech synthesis. SpeD 2011: 1-6
Coauthor Index
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