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Tamás Grósz

4 accepted papers

2024

Collecting Linguistic Resources for Assessing Children’s Pronunciation of Nordic Languages

Anne Marte Haug Olstad, Anna Smolander, Sofia Strömbergsson, Sari Ylinen, Minna Lehtonen, Mikko Kurimo +5
COLING 2024main

This paper reports on the experience collecting a number of corpora of Nordic languages spoken by children. The aim of the data collection is providing annotated data to develop and evaluate computer assisted pronunciation assessment systems both for non-native children learning a Nordic language (L…

Cited by 2Source ↗PDF ↗Scholar ↗
2024

Investigating the Clusters Discovered By Pre-Trained AV-HuBERT

Anja Virkkunen, Marek Sarvas, Guangpu Huang, Tamás Grósz, Mikko Kurimo
ICASSP 2024accepted

Self-supervised models, such as HuBERT and its audio-visual version AV-HuBERT, have demonstrated excellent performance on various tasks. The main factor for their success is the pre-training procedure, which requires only raw data without human transcription. During the self-supervised pre-training…

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2018

F0 Estimation for DNN-Based Ultrasound Silent Speech Interfaces

Tamás Grósz, Gábor Gosztolya, László Tóth, Tamás Gábor Csapó, Alexandra Markó
ICASSP 2018accepted

State-of-the-art silent speech interface systems apply vocoders to generate the speech signal directly from articulatory data. Most of these approaches concentrate on estimating just the spectral features of the vocoder, and use the original F0, a constant F0 or white noise as excitation. This solut…

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2015

Building context-dependent DNN acoustic models using Kullback-Leibler divergence-based state tying

Gábor Gosztolya, Tamás Grósz, László Tóth, David Imseng
ICASSP 2015accepted

Deep neural network (DNN) based speech recognizers have recently replaced Gaussian mixture (GMM) based systems as the state-of-the-art. HMM/DNN systems have kept many refinements of the HMM/GMM framework, even though some of these may be suboptimal for them. One such example is the creation of conte…

Cited by 0Source ↗Scholar ↗