Aleksandr Laptev

Orcid: 0000-0002-4690-705X

According to our database1, Aleksandr Laptev authored at least 13 papers between 2020 and 2024.

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

Timeline

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Bibliography

2024
Fast Context-Biasing for CTC and Transducer ASR models with CTC-based Word Spotter.
CoRR, 2024

2023
The CHiME-7 Challenge: System Description and Performance of NeMo Team's DASR System.
CoRR, 2023

Confidence-based Ensembles of End-to-End Speech Recognition Models.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

Powerful and Extensible WFST Framework for Rnn-Transducer Losses.
Proceedings of the IEEE International Conference on Acoustics, 2023

2022
Fast Entropy-Based Methods of Word-Level Confidence Estimation for End-to-End Automatic Speech Recognition.
Proceedings of the IEEE Spoken Language Technology Workshop, 2022

CTC Variations Through New WFST Topologies.
Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

2021
Dynamic Acoustic Unit Augmentation with BPE-Dropout for Low-Resource End-to-End Speech Recognition.
Sensors, 2021

LT-LM: A Novel Non-Autoregressive Language Model for Single-Shot Lattice Rescoring.
Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

2020
Techniques for Vocabulary Expansion in Hybrid Speech Recognition Systems.
CoRR, 2020

Exploration of End-to-End ASR for OpenSTT - Russian Open Speech-to-Text Dataset.
Proceedings of the Speech and Computer - 22nd International Conference, 2020

Target-Speaker Voice Activity Detection: A Novel Approach for Multi-Speaker Diarization in a Dinner Party Scenario.
Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

Towards a Competitive End-to-End Speech Recognition for CHiME-6 Dinner Party Transcription.
Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

You Do Not Need More Data: Improving End-To-End Speech Recognition by Text-To-Speech Data Augmentation.
Proceedings of the 13th International Congress on Image and Signal Processing, 2020


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