198 citations · 221 across the 6 of their papers we have counts for
7 papers
Flow Matching-Based Speech Source Separation with Best-of-N Biometric Sampling
Anastasia Zorkina, Alexandr Anikin, Nikita Khmelev +5
Single-channel speech separation remains challenging for real-world deployment due to source permutation ambiguity, sampling variability of generative models, and the difficulty of…
STCON System for the CHiME-8 Challenge
Anton Mitrofanov, Tatiana Prisyach, Tatiana Timofeeva +13
This paper describes the STCON system for the CHiME-8 Challenge Task 1 (DASR) aimed at distant automatic speech transcription and diarization with multiple recording devices. Our m…
LT-LM: a novel non-autoregressive language model for single-shot lattice rescoring
Anton Mitrofanov, Mariya Korenevskaya, Ivan Podluzhny +7
Neural network-based language models are commonly used in rescoring approaches to improve the quality of modern automatic speech recognition (ASR) systems. Most of the existing met…
Target-Speaker Voice Activity Detection: a Novel Approach for Multi-Speaker Diarization in a Dinner Party Scenario
Ivan Medennikov, Maxim Korenevsky, Tatiana Prisyach +9
Speaker diarization for real-life scenarios is an extremely challenging problem. Widely used clustering-based diarization approaches perform rather poorly in such conditions, mainl…
Medical code prediction with multi-view convolution and description-regularized label-dependent attention
Najmeh Sadoughi, Greg P. Finley, James Fone +6
A ubiquitous task in processing electronic medical data is the assignment of standardized codes representing diagnoses and/or procedures to free-text documents such as medical repo…
Exploring End-to-End Techniques for Low-Resource Speech Recognition
Vladimir Bataev, Maxim Korenevsky, Ivan Medennikov +1
In this work we present simple grapheme-based system for low-resource speech recognition using Babel data for Turkish spontaneous speech (80 hours). We have investigated different…
Investigation of Using VAE for i-Vector Speaker Verification
Timur Pekhovsky, Maxim Korenevsky
New system for i-vector speaker recognition based on variational autoencoder (VAE) is investigated. VAE is a promising approach for developing accurate deep nonlinear generative mo…