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Péter Mihajlik
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2020 – today
- 2024
- [c30]Péter Mihajlik, Katalin Mády, Anna Kohári, Fruzsina Sára Fruzsina, Gábor Kiss, Tekla Etelka Gráczi, A. Seza Dogruöz:
Is Spoken Hungarian Low-resource?: A Quantitative Survey of Hungarian Speech Data Sets. LREC/COLING 2024: 9382-9388 - 2023
- [c29]Julian Linke, Mate Kadar, Gergely Dosinszky, Péter Mihajlik, Gernot Kubin, Barbara Schuppler
:
What do self-supervised speech representations encode? An analysis of languages, varieties, speaking styles and speakers. INTERSPEECH 2023: 5371-5375 - 2022
- [c28]Péter Mihajlik
, András Balog, Tekla Etelka Gráczi, Anna Kohári, Balázs Tarján, Katalin Mády:
BEA-Base: A Benchmark for ASR of Spontaneous Hungarian. LREC 2022: 1970-1977 - [i4]Péter Mihajlik, András Balog, Tekla Etelka Gráczi, Anna Kohári, Balázs Tarján, Katalin Mády:
BEA-Base: A Benchmark for ASR of Spontaneous Hungarian. CoRR abs/2202.00601 (2022) - 2020
- [c27]Balázs Tarján, György Szaszák, Tibor Fegyó, Péter Mihajlik
:
Improving Real-time Recognition of Morphologically Rich Speech with Transformer Language Model. CogInfoCom 2020: 491-496 - [c26]Balázs Tarján
, György Szaszák, Tibor Fegyó, Péter Mihajlik:
On the Effectiveness of Neural Text Generation Based Data Augmentation for Recognition of Morphologically Rich Speech. TDS 2020: 437-445 - [i3]Balázs Tarján, György Szaszák, Tibor Fegyó, Péter Mihajlik:
On the Effectiveness of Neural Text Generation based Data Augmentation for Recognition of Morphologically Rich Speech. CoRR abs/2006.05129 (2020) - [i2]Balázs Tarján, György Szaszák, Tibor Fegyó, Péter Mihajlik:
Deep Transformer based Data Augmentation with Subword Units for Morphologically Rich Online ASR. CoRR abs/2007.06949 (2020)
2010 – 2019
- 2019
- [c25]Balázs Tarján, György Szaszák, Tibor Fegyó, Péter Mihajlik:
N-gram Approximation of LSTM Recurrent Language Models for Single-pass Recognition of Hungarian Call Center Conversations. CogInfoCom 2019: 131-136 - [c24]Balázs Tarján
, György Szaszák, Tibor Fegyó, Péter Mihajlik:
Investigation on N-Gram Approximated RNNLMs for Recognition of Morphologically Rich Speech. SLSP 2019: 223-234 - [i1]Balázs Tarján, György Szaszák, Tibor Fegyó, Péter Mihajlik:
Investigation on N-gram Approximated RNNLMs for Recognition of Morphologically Rich Speech. CoRR abs/1907.06407 (2019) - 2017
- [c23]Péter Mihajlik
, Lili Szabó, Balázs Tarján
, András Balog, Krisztina Rábai:
First Results in Developing a Medieval Latin Language Charter Dictation System for the East-Central Europe Region. INTERSPEECH 2017: 2058-2062 - [c22]Lili Szabó, Péter Mihajlik, András Balog, Tibor Fegyó:
Unified Simplified Grapheme Acoustic Modeling for Medieval Latin LVCSR. TSD 2017: 420-428 - 2015
- [c21]Ádam Varga, Balázs Tarján
, Zoltán Tobler, György Szaszák, Tibor Fegyó, Csaba Bordás, Péter Mihajlik
:
Automatic Close Captioning for Live Hungarian Television Broadcast Speech: A Fast and Resource-Efficient Approach. SPECOM 2015: 105-112 - 2014
- [j4]Gellért Sárosi, Balázs Tarján
, Tibor Fegyó, Péter Mihajlik:
Automated transcription of conversational Call Center speech - with respect to non-verbal acoustic events. Intell. Decis. Technol. 8(4): 265-275 (2014) - [c20]Lili Szabó, Balázs Tarján
, Péter Mihajlik:
Writing with speech: A qualitative user evaluation study. CogInfoCom 2014: 355-360 - [c19]Balázs Tarján, Tibor Fegyó, Péter Mihajlik:
A bilingual study on the prediction of morph-based improvement. SLTU 2014: 131-138 - 2013
- [c18]Péter Mihajlik, András Balog:
Lightly supervised acoustic model training for imprecisely and asynchronously transcribed speech. SpeD 2013: 1-5 - [c17]Balázs Tarján
, Gellért Sárosi, Tibor Fegyó, Péter Mihajlik
:
Improved recognition of Hungarian call center conversations. SpeD 2013: 1-6 - 2012
- [c16]Balázs Tarján
, Tamás Mozsolics, András Balog, D. Halmos, Tibor Fegyó, Péter Mihajlik
:
Broadcast news transcription in Central-East European languages. CogInfoCom 2012: 59-64 - [c15]Gellért Sárosi, Balázs Tarján
, András Balog, Tamás Mozsolics, Péter Mihajlik, Tibor Fegyó:
On modeling non-word events in Large Vocabulary Continuous Speech Recognition. CogInfoCom 2012: 649-653 - [c14]Éva Székely, Tamás Gábor Csapó
, Bálint Tóth, Péter Mihajlik
, Julie Carson-Berndsen:
Synthesizing expressive speech from amateur audiobook recordings. SLT 2012: 297-302 - 2011
- [c13]Gellért Sárosi, Mihály Mozsáry, Péter Mihajlik, Tibor Fegyó:
Comparison of feature extraction methods for speech recognition in noise-free and in traffic noise environment. SpeD 2011: 1-8 - 2010
- [j3]László Tóth, Balázs Tarján, Gellért Sárosi, Péter Mihajlik:
Speech Recognition Experiments with Audiobooks. Acta Cybern. 19(4): 695-713 (2010) - [j2]Péter Mihajlik
, Zoltán Tüske, Balázs Tarján
, Bottyán Németh, Tibor Fegyó:
Improved Recognition of Spontaneous Hungarian Speech - Morphological and Acoustic Modeling Techniques for a Less Resourced Task. IEEE Trans. Speech Audio Process. 18(6): 1588-1600 (2010) - [c12]Gellért Sárosi, Tamás Mozsolics, Balázs Tarján
, András Balog, Péter Mihajlik, Tibor Fegyó:
Recognition of Multiple Language Voice Navigation Queries in Traffic Situations. COST 2102 Conference 2010: 199-213 - [c11]Balázs Tarján, Péter Mihajlik:
On morph-based LVCSR improvements. SLTU 2010: 10-16
2000 – 2009
- 2009
- [c10]Péter Mihajlik, Balázs Tarján, Zoltán Tüske, Tibor Fegyó:
Investigation of morph-based speech recognition improvements across speech genres. INTERSPEECH 2009: 2687-2690 - 2008
- [c9]Géza Németh
, Gábor Olaszy, Mátyás Bartalis, Géza Kiss, Csaba Zainkó, Péter Mihajlik, Csaba Haraszti:
Automated Drug Information System for Aged and Visually Impaired Persons. ICCHP 2008: 238-241 - 2007
- [c8]Péter Mihajlik
, Tibor Fegyó, Zoltán Tüske, Pavel Ircing:
A morpho-graphemic approach for the recognition of spontaneous speech in agglutinative languages - like Hungarian. INTERSPEECH 2007: 1497-1500 - [c7]Géza Németh, Gábor Olaszy, Mátyás Bartalis, Géza Kiss, Csaba Zainkó, Péter Mihajlik:
Speech based drug information system for aged and visually impaired persons. INTERSPEECH 2007: 2533-2536 - [c6]Péter Mihajlik
, Tibor Fegyó, Bottyán Németh, Zoltán Tüske, Viktor Trón:
Towards Automatic Transcription of Large Spoken Archives in Agglutinating Languages - Hungarian ASR for the MALACH Project. TSD 2007: 342-349 - 2005
- [c5]Zoltán Tüske, Péter Mihajlik
, Zoltán Tobler, Tibor Fegyó:
Robust voice activity detection based on the entropy of noise-suppressed spectrum. INTERSPEECH 2005: 245-248 - [c4]Péter Mihajlik
, Zoltán Tobler, Zoltán Tüske, Géza Gordos:
Evaluation and optimization of noise robust front-end technologies for the automatic recognition of Hungarian telephone speech. INTERSPEECH 2005: 2677-2680 - 2003
- [c3]Tibor Fegyó, Péter Mihajlik, Péter Tatai:
Comparative study on hungarian acoustic model sets and training methods. INTERSPEECH 2003: 829-832 - [c2]Tibor Fegyó, Péter Mihajlik
, Máté Szarvas, Péter Tatai, Gábor Tatai:
Voxenter^TM - intelligent voice enabled call center for hungarian. INTERSPEECH 2003: 1905-1908 - 2001
- [c1]Tibor Fegyó, Péter Mihajlik
, Péter Tatai, Géza Gordos:
Pronunciation modeling in hungarian number recognition. INTERSPEECH 2001: 1465-1468 - 2000
- [j1]Máté Szarvas, Tibor Fegyó, Péter Mihajlik, Péter Tatai:
Automatic Recognition of Hungarian: Theory And Practice. Int. J. Speech Technol. 3(3-4): 237-251 (2000)
Coauthor Index
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last updated on 2024-08-06 22:03 CEST by the dblp team
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