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2020 – today
- 2023
[c16]Lukás Mateju, Jan Nouza, Petr Cerva, Jindrich Zdánský, Frantisek Kynych:
Combining Multilingual Resources and Models to Develop State-of-the-Art E2E ASR for Swedish. INTERSPEECH 2023: 3252-3256- [c15]Frantisek Kynych, Jindrich Zdánský, Petr Cerva, Lukás Mateju:
Online Speaker Diarization Using Optimized SE-ResNet Architecture. TSD 2023: 176-187 - [c14]Jan Nouza, Lukás Mateju, Petr Cerva, Jindrich Zdánský:
Developing State-of-the-Art End-to-End ASR for Norwegian. TSD 2023: 200-213 - 2022
- [c13]Lukás Mateju, Frantisek Kynych, Petr Cerva, Jirí Málek, Jindrich Zdánský:
Overlapped Speech Detection in Broadcast Streams Using X-vectors. INTERSPEECH 2022: 4606-4610 - 2021
- [j2]Petr Cerva, Lukás Mateju, Jindrich Zdánský, Radek Safarík, Jan Nouza:
Identification of related languages from spoken data: Moving from off-line to on-line scenario. Comput. Speech Lang. 68: 101180 (2021) - [j1]Lukás Mateju, David Griol, Zoraida Callejas, José Manuel Molina, Araceli Sanchis
:
An empirical assessment of deep learning approaches to task-oriented dialog management. Neurocomputing 439: 327-339 (2021) - [c12]Lukás Mateju, Frantisek Kynych, Petr Cerva, Jindrich Zdánský, Jirí Málek:
Using X-Vectors for Speech Activity Detection in Broadcast Streams. Interspeech 2021: 1474-1478 - [c11]Petr Cerva, Lukás Mateju, Frantisek Kynych, Jindrich Zdánský, Jan Nouza:
Identification of Scandinavian Languages from Speech Using Bottleneck Features and X-Vectors. TDS 2021: 371-381 - [i1]Lukás Mateju, David Griol, Zoraida Callejas, José Manuel Molina, Araceli Sanchis:
An empirical assessment of deep learning approaches to task-oriented dialog management. CoRR abs/2108.03478 (2021)
2010 – 2019
- 2019
- [c10]Lukás Mateju, Petr Cerva, Jindrich Zdánský:
An Approach to Online Speaker Change Point Detection Using DNNs and WFSTs. INTERSPEECH 2019: 649-653 - 2018
- [c9]Lukás Mateju, Petr Cerva, Jindrich Zdánský, Radek Safarík:
Using Deep Neural Networks for Identification of Slavic Languages from Acoustic Signal. INTERSPEECH 2018: 1803-1807 - [c8]Radek Safarík, Lukás Mateju, Lenka Weingartová:
The Influence of Errors in Phonetic Annotations on Performance of Speech Recognition System. TSD 2018: 419-427 - [c7]Radek Safarík, Lukás Mateju:
Automatic Development of ASR System for an Under-Resourced Language. TSP 2018: 1-4 - 2017
- [c6]Lukás Mateju, Petr Cerva, Jindrich Zdánský, Jirí Málek:
Speech Activity Detection in online broadcast transcription using Deep Neural Networks and Weighted Finite State Transducers. ICASSP 2017: 5460-5464 - [c5]Radek Safarík, Lukás Mateju:
The Impact of Inaccurate Phonetic Annotations on Speech Recognition Performance. TSD 2017: 402-410 - 2016
- [c4]Lukás Mateju, Petr Cerva, Jindrich Zdánský:
Investigation into the Use of WFSTs and DNNs for Speech Activity Detection in Broadcast Data Transcription. ICETE (Selected Papers) 2016: 341-358 - [c3]Lukás Mateju, Petr Cerva, Jindrich Zdánský:
Study on the Use of Deep Neural Networks for Speech Activity Detection in Broadcast Recordings. SIGMAP 2016: 45-51 - [c2]Marek Bohác, Lukás Mateju, Michal Rott, Radek Safarík:
Automatic Syllabification and Syllable Timing of Automatically Recognized Speech - for Czech. TSD 2016: 540-547 - [c1]Radek Safarík, Lukás Mateju:
Impact of phonetic annotation precision on automatic speech recognition systems. TSP 2016: 311-314
Coauthor Index
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