collaborators

5 papers

eess.AS2025

Unified Semi-Supervised Pipeline for Automatic Speech Recognition

Nune Tadevosyan, Nikolay Karpov, Andrei Andrusenko +2

Automatic Speech Recognition has been a longstanding research area, with substantial efforts dedicated to integrating semi-supervised learning due to the scarcity of labeled datase…

eess.AS2025

Pushing the Limits of Beam Search Decoding for Transducer-based ASR models

Lilit Grigoryan, Vladimir Bataev, Andrei Andrusenko +3

Transducer models have emerged as a promising choice for end-to-end ASR systems, offering a balanced trade-off between recognition accuracy, streaming capabilities, and inference s…

eess.AS2025

NGPU-LM: GPU-Accelerated N-Gram Language Model for Context-Biasing in Greedy ASR Decoding

Vladimir Bataev, Andrei Andrusenko, Lilit Grigoryan +3

Statistical n-gram language models are widely used for context-biasing tasks in Automatic Speech Recognition (ASR). However, existing implementations lack computational efficiency…

eess.AS20241 cited

Fast Context-Biasing for CTC and Transducer ASR models with CTC-based Word Spotter

Andrei Andrusenko, Aleksandr Laptev, Vladimir Bataev +2

Accurate recognition of rare and new words remains a pressing problem for contextualized Automatic Speech Recognition (ASR) systems. Most context-biasing methods involve modificati…

cs.CL2023

SALM: Speech-augmented Language Model with In-context Learning for Speech Recognition and Translation

Zhehuai Chen, He Huang, Andrei Andrusenko +6

We present a novel Speech Augmented Language Model (SALM) with {\em multitask} and {\em in-context} learning capabilities. SALM comprises a frozen text LLM, a audio encoder, a moda…