Publications

Found 304 results
[ Author(Asc)] Keyword Title Type Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
G
Gröger HDietmar, Turán G.  1993.  A Liniear lower bound for the size of threshold circuits. Bulletin of the EATCS. 50:220–221.
Gosztoya G, Kocsor A, Tóth L, Felföldi L.  2002.  Various Robust Search Methods in a Hungarian Speech recognition System. Conference of PhD students on Computer Sciences, Volume of Extended Abstracts. :35.
Gosztolya G, Tóth L.  2018.  A feature selection-based speaker clustering method for paralinguistic tasks. Pattern Analysis and Applications. 21:193–204.
Gosztolya G, Kocsor A, Tóth L, Felföldi L.  2003.  Various Robust Search Methods in a Hungarian Speech Recognition System. Acta Cybernetica. 16:229-240.
Gosztolya G, Kocsor A.  2003.  Improving the Multi-stack Decoding Algorithm in a Segment-based Speech Recognizer. Proceedings of the 16th International Conference on Developments in Applied Artificial Intelligence. :744–749.
Gosztolya G, Grósz T, Tóth L.  2020.  Social Signal Detection by Probabilistic Sampling DNN Training. IEEE Transactions on Affective Computing. 10:164–177.
Gosztolya G.  2020.  Using the Fisher Vector Representation for Audio-based Emotion Recognition. Acta Polytechnica Hungarica. 17:7–23.
Gosztolya G, Busa-Fekete R, Grósz T, Tóth L.  2017.  DNN-Based Feature Extraction and Classifier Combination for Child-Directed Speech, Cold and Snoring Identification. Proceedings of Interspeech. :3522–3526.
Gosztolya G, Pintér Á, Tóth L, Grósz T, Markó A, Csapó TGábor.  2019.  Autoencoder-Based Articulatory-to-Acoustic Mapping for Ultrasound Silent Speech Interfaces. Proceedings of IJCNN.
Gosztolya G, Grósz T, Tóth L.  2016.  GMM-Free Flat Start Sequence-Discriminative DNN Training. Proceedings of Interspeech. :3409–3413.
Gosztolya G, Kocsor A, Tóth L, Felföldi L.  2003.  Various Robust Search Methods in a Hungarian Speech Recognition System. Acta Cybernetica. 16:229–240.
Gosztolya G, Busa-Fekete R.  2019.  Calibrating AdaBoost for Phoneme Classification. Soft Computing. 23:115–128.
Gosztolya G, Tóth L.  2019.  Calibrating DNN Posterior Probability Estimates of HMM/DNN Models to Improve Social Signal Detection From Audio Data. Proceedings of Interspeech. :515–519.
Gosztolya G, Grósz T, Tóth L, Markó A, Csapó TGábor.  2020.  Applying DNN Adaptation to Reduce the Session Dependency of Ultrasound Tongue Imaging-based Silent Speech Interfaces. Acta Polytechnica Hungarica. 17:109–124.
Gosztolya G.  2019.  Using the Bag-of-Audio-Word Feature Representation of ASR DNN Posteriors for Paralinguistic Classification. Proceedings of Interspeech. :2413–2417.
Gosztolya G, Vincze V, Tóth L, Pákáski M, Kálmán J, Hoffmann I.  2019.  Identifying Mild Cognitive Impairment and mild Alzheimer’s disease based on spontaneous speech using ASR and linguistic features. Computer, Speech & Language. 53:181–197.
Gosztolya G, Tóth L.  2017.  DNN-based Feature Extraction for Conflict Intensity Estimation from Speech. IEEE Signal Processing Letters. 24:1837–1841.
Gosztolya G.  2019.  Posterior-Thresholding Feature Extraction for Paralinguistic Speech Classification. Knowledge-Based Systems. 186
Gosztolya G.  2019.  Using Fisher Vector and Bag-of-Audio-Words Representations to Identify Styrian Dialects, Sleepiness, Baby & Orca Sounds. Proceedings of Interspeech. :2413–2417.
Goldsmith J, Sloan RH, Turán G.  2002.  Theory Revision with Queries: DNF Formulas. Machine Learning. 47:257–295.
Gergely T, Balogh G, Horvath F, Vancsics B, Beszedes A, Gyimothy T.  2019.  Differences between a static and a dynamic test-to-code traceability recovery method. SOFTWARE QUALITY JOURNAL. 27:797-822.
Gergely T, Balogh G, Horváth F, Vancsics B, Beszédes Á, Gyimóthy T.  2018.  Analysis of Static and Dynamic Test-to-code Traceability Information. Acta Cybernetica. 23:903-919.
Gábor S, Gábor A, Nagy C, Ferenc R, Gyimóthy T.  2017.  Empirical Study on Refactoring Large-scale Industrial Systems and Its Effects on Maintainability. Journal of Systems and Software. 129:107–126.

Pages