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ORCIDHari Krishna Vydana
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2020 – today
- 2024
[c19]Stefano Bannò, Hari Krishna Vydana, Kate M. Knill, Mark J. F. Gales:
Can GPT-4 do L2 analytic assessment? BEA 2024: 149-164- [i7]Stefano Bannò, Hari Krishna Vydana, Kate M. Knill, Mark J. F. Gales:
Can GPT-4 do L2 analytic assessment? CoRR abs/2404.18557 (2024) - 2022
- [j4]Ekaterina Egorova
, Hari Krishna Vydana, Lukás Burget, Jan Honza Cernocký:
Spelling-Aware Word-Based End-to-End ASR. IEEE Signal Process. Lett. 29: 1729-1733 (2022) - 2021
- [j3]Hari Krishna Vydana, Anil Kumar Vuppala:
Detection of Fricative Landmarks Using Spectral Weighting: A Temporal Approach. Circuits Syst. Signal Process. 40(5): 2376-2399 (2021) - [c18]Hari Krishna Vydana, Martin Karafiát, Katerina Zmolíková, Lukás Burget, Honza Cernocký:
Jointly Trained Transformers Models for Spoken Language Translation. ICASSP 2021: 7513-7517 - [c17]Ekaterina Egorova, Hari Krishna Vydana, Lukás Burget, Jan Cernocký:
Out-of-Vocabulary Words Detection with Attention and CTC Alignments in an End-to-End ASR System. Interspeech 2021: 2901-2905 - [c16]Hari Krishna Vydana, Martin Karafiát, Lukás Burget, Jan Cernocký:
The IWSLT 2021 BUT Speech Translation Systems. IWSLT 2021: 75-83 - [i6]Hari Krishna Vydana, Martin Karafiát, Lukás Burget, Honza Cernocký:
The IWSLT 2021 BUT Speech Translation Systems. CoRR abs/2107.06155 (2021) - 2020
- [i5]Martin Karafiát, Murali Karthick Baskar, Igor Szöke, Hari Krishna Vydana, Karel Veselý, Jan Honza Cernocký:
BUT Opensat 2019 Speech Recognition System. CoRR abs/2001.11360 (2020) - [i4]Hari Krishna Vydana, Martin Karafiát, Katerina Zmolíková, Lukás Burget, Honza Cernocký:
Jointly Trained Transformers models for Spoken Language Translation. CoRR abs/2004.12111 (2020) - [i3]Hari Krishna Vydana, Lukás Burget, Jan Cernocký:
A Technical Report: BUT Speech Translation Systems. CoRR abs/2010.11593 (2020)
2010 – 2019
- 2019
- [c15]Tirusha Mandava, Ravi Kumar Vuddagiri, Hari Krishna Vydana, Anil Kumar Vuppala:
An Investigation of LSTM-CTC based Joint Acoustic Model for Indian Language Identification. ASRU 2019: 389-396 - [c14]Ravi Kumar Vuddagiri, Tirusha Mandava, Hari Krishna Vydana, Anil Kumar Vuppala:
Multi-Head Self-Attention Networks for Language Identification. IC3 2019: 1-5 - [c13]Lucas Ondel, Hari Krishna Vydana, Lukás Burget, Jan Cernocký:
Bayesian Subspace Hidden Markov Model for Acoustic Unit Discovery. INTERSPEECH 2019: 261-265 - [i2]Lucas Ondel, Hari Krishna Vydana, Lukás Burget, Jan Cernocký:
Bayesian Subspace Hidden Markov Model for Acoustic Unit Discovery. CoRR abs/1904.03876 (2019) - 2018
- [j2]Ravi Kumar Vuddagiri, Hari Krishna Vydana, Anil Kumar Vuppala:
Curriculum learning based approach for noise robust language identification using DNN with attention. Expert Syst. Appl. 110: 290-297 (2018) - [c12]Hari Krishna Vydana, Krishna Gurugubelli, Vishnu Vidyadhara Raju Vegesna, Anil Kumar Vuppala:
An Exploration towards Joint Acoustic Modeling for Indian Languages: IIIT-H Submission for Low Resource Speech Recognition Challenge for Indian Languages, INTERSPEECH 2018. INTERSPEECH 2018: 3192-3196 - [c11]Ravi Kumar Vuddagiri, Krishna Gurugubelli, Priyam Jain, Hari Krishna Vydana, Anil Kumar Vuppala:
IIITH-ILSC Speech Database for Indain Language Identification. SLTU 2018: 56-60 - [c10]Hari Krishna Vydana, Sivanand Achanta, Anil Kumar Vuppala:
Incorporating Speaker Normalizing Capabilities to an End-to-End Speech Recognition System. SLTU 2018: 172-176 - [c9]Ravi Kumar Vuddagiri, Hari Krishna Vydana, Anil Kumar Vuppala:
Improved Language Identification Using Stacked SDC Features and Residual Neural Network. SLTU 2018: 210-214 - 2017
- [c8]Vishnu Vidyadhara Raju Vegesna, Hari Krishna Vydana, Suryakanth V. Gangashetty, Anil Kumar Vuppala:
Importance of non-uniform prosody modification for speech recognition in emotion conditions. APSIPA 2017: 573-576 - [c7]Hari Krishna Vydana, Anil Kumar Vuppala:
Residual neural networks for speech recognition. EUSIPCO 2017: 543-547 - [c6]Brij Mohan Lal Srivastava, Hari Krishna Vydana, Anil Kumar Vuppala, Manish Shrivastava:
Significance of neural phonotactic models for large-scale spoken language identification. IJCNN 2017: 2144-2151 - [c5]Vishnu Vidyadhara Raju Vegesna, Krishna Gurugubelli, Hari Krishna Vydana, Bhargav Pulugandla, Manish Shrivastava, Anil Kumar Vuppala:
DNN-HMM Acoustic Modeling for Large Vocabulary Telugu Speech Recognition. MIKE 2017: 189-197 - [c4]Hari Krishna Vydana, Anil Kumar Vuppala:
Investigative study of various activation functions for speech recognition. NCC 2017: 1-5 - 2016
- [j1]Hari Krishna Vydana, Sudarsana Reddy Kadiri, Anil Kumar Vuppala:
Vowel-Based Non-uniform Prosody Modification for Emotion Conversion. Circuits Syst. Signal Process. 35(5): 1643-1663 (2016) - [c3]Ramakrishna Thirumuru, Hari Krishna Vydana, Suryakanth V. Gangashetty, Anil Kumar Vuppala:
A Study on Vowel Region Detection from a Continuous Speech. MIKE 2016: 74-82 - 2015
- [c2]Hari Krishna Vydana, Vishnu Vidyadhara Raju Vegesna, Suryakanth V. Gangashetty, Anil Kumar Vuppala:
Significance of Emotionally Significant Regions of Speech for Emotive to Neutral Conversion. MIKE 2015: 287-296 - [c1]Ravi Kumar Vuddagiri, Hari Krishna Vydana, Jiteesh Varma Bhupathiraju, Suryakanth V. Gangashetty, Anil Kumar Vuppala:
Improved Language Identification in Presence of Speech Coding. MIKE 2015: 312-322 - [i1]Brij Mohan Lal Srivastava, Hari Krishna Vydana, Anil Kumar Vuppala, Manish Shrivastava:
A language model based approach towards large scale and lightweight language identification systems. CoRR abs/1510.03602 (2015)
Coauthor Index
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last updated on 2024-09-28 02:24 CEST by the dblp team
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