Petar S. Aleksic

According to our database1, Petar S. Aleksic authored at least 29 papers between 2002 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
High-precision Voice Search Query Correction via Retrievable Speech-text Embedings.
CoRR, 2024

2021
Improving Entity Recall in Automatic Speech Recognition with Neural Embeddings.
Proceedings of the IEEE International Conference on Acoustics, 2021

2020
Mixed Case Contextual ASR Using Capitalization Masks.
Proceedings of the Interspeech 2020, 2020

Multistate Encoding with End-To-End Speech RNN Transducer Network.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Incorporating Written Domain Numeric Grammars into End-To-End Contextual Speech Recognition Systems for Improved Recognition of Numeric Sequences.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Contextual Recovery of Out-of-Lattice Named Entities in Automatic Speech Recognition.
Proceedings of the Interspeech 2019, 2019

2018
Contextual Speech Recognition in End-to-end Neural Network Systems Using Beam Search.
Proceedings of the Interspeech 2018, 2018

Semantic Lattice Processing in Contextual Automatic Speech Recognition for Google Assistant.
Proceedings of the Interspeech 2018, 2018

Cross-Lingual Phoneme Mapping for Language Robust Contextual Speech Recognition.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017
Rescoring-Aware Beam Search for Reduced Search Errors in Contextual Automatic Speech Recognition.
Proceedings of the Interspeech 2017, 2017

Keyword spotting for Google assistant using contextual speech recognition.
Proceedings of the 2017 IEEE Automatic Speech Recognition and Understanding Workshop, 2017

2016
Contextual language model adaptation using dynamic classes.
Proceedings of the 2016 IEEE Spoken Language Technology Workshop, 2016

Voice search language model adaptation using contextual information.
Proceedings of the 2016 IEEE Spoken Language Technology Workshop, 2016

Unsupervised context learning for speech recognition.
Proceedings of the 2016 IEEE Spoken Language Technology Workshop, 2016

2015
Lip Movement Recognition.
Proceedings of the Encyclopedia of Biometrics, Second Edition, 2015

Bringing contextual information to google speech recognition.
Proceedings of the INTERSPEECH 2015, 2015

Improved recognition of contact names in voice commands.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

2009
Lip Movement Recognition.
Proceedings of the Encyclopedia of Biometrics, 2009

2006
Automatic facial expression recognition using facial animation parameters and multistream HMMs.
IEEE Trans. Inf. Forensics Secur., 2006

Audio-Visual Biometrics.
Proc. IEEE, 2006

2005
Comparison of MPEG-4 facial animation parameter groups with respect to audio-visual speech recognition performance.
Proceedings of the 2005 International Conference on Image Processing, 2005

2004
Speech-to-video synthesis using MPEG-4 compliant visual features.
IEEE Trans. Circuits Syst. Video Technol., 2004

Inner lip feature extraction for MPEG-4 facial animation.
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

Comparison of low- and high-level visual features for audio-visual continuous automatic speech recognition.
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

2003
Product HMMs for audio-visual continuous speech recognition using facial animation parameters.
Proceedings of the 2003 IEEE International Conference on Multimedia and Expo, 2003

Speech-to-video synthesis using facial animation parameters.
Proceedings of the 2003 International Conference on Image Processing, 2003

2002
Audio-Visual Speech Recognition Using MPEG-4 Compliant Visual Features.
EURASIP J. Adv. Signal Process., 2002

Lip Tracking for MPEG-4 Facial Animation.
Proceedings of the 4th IEEE International Conference on Multimodal Interfaces (ICMI 2002), 2002

Audio-visual continuous speech recognition using MPEG-4 compliant visual features.
Proceedings of the 2002 International Conference on Image Processing, 2002


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