Torbjørn Svendsen — accepted AI-conference 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…

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2023

Using Modified Adult Speech as Data Augmentation for Child Speech Recognition

Zijian Fan, Xinwei Cao, Giampiero Salvi, Torbjørn Svendsen

ICASSP 2023accepted

Data augmentation is a technique which enhances the size and quality of training data such that deep learning or machine learning models can achieve better performance. This paper proposes a novel way of applying data augmentation for child speech recognition in the low data resource scenario. Data…

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2021

A Two-Stage Deep Modeling Approach to Articulatory Inversion

Abdolreza Sabzi Shahrebabaki, Negar Olfati, Ali Shariq Imran, Magne Hallstein Johnsen, Sabato Marco Siniscalchi, Torbjørn Svendsen

ICASSP 2021accepted

This paper proposes a two-stage deep feed-forward neural network (DNN) to tackle the acoustic-to-articulatory inversion (AAI) problem. DNNs are a viable solution for the AAI task, but the temporal continuity of the estimated articulatory values has not been exploited properly when a DNN is employed.…

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