Zobrazeno 1 - 10
of 182
pro vyhledávání: '"Mikko Kurimo"'
Autor:
Yaroslav Getman, Nhan Phan, Ragheb Al-Ghezi, Ekaterina Voskoboinik, Mittul Singh, Tamas Grosz, Mikko Kurimo, Giampiero Salvi, Torbjorn Svendsen, Sofia Strombergsson, Anna Smolander, Sari Ylinen
Publikováno v:
IEEE Access, Vol 11, Pp 86025-86037 (2023)
Computer-assisted Language Learning (CALL) is a rapidly developing area accelerated by advancements in the field of AI. A well-designed and reliable CALL system allows students to practice language skills, like pronunciation, any time outside of the
Externí odkaz:
https://doaj.org/article/442dc31a24f345a3a3ab0c5517d82a2e
Publikováno v:
Frontiers in Human Neuroscience, Vol 17 (2023)
Children with dyslexia often face difficulties in learning foreign languages, which is reflected as weaker neural activation. However, digital language-learning applications could support learning-induced plastic changes in the brain. Here we aimed t
Externí odkaz:
https://doaj.org/article/4e1144fbb9684e9492d71e528e6d44d2
Autor:
Sari Ylinen, Anna-Riikka Smolander, Reima Karhila, Sofoklis Kakouros, Jari Lipsanen, Minna Huotilainen, Mikko Kurimo
Publikováno v:
Frontiers in Education, Vol 6 (2021)
Digital and mobile devices enable easy access to applications for the learning of foreign languages. However, experimental studies on the effectiveness of these applications are scarce. Moreover, it is not understood whether the effects of speech and
Externí odkaz:
https://doaj.org/article/a5a9d04a823740eab964544ecd3553ef
Publikováno v:
NeuroImage, Vol 219, Iss , Pp 116936- (2020)
Natural speech builds on contextual relations that can prompt predictions of upcoming utterances. To study the neural underpinnings of such predictive processing we asked 10 healthy adults to listen to a 1-h-long audiobook while their magnetoencephal
Externí odkaz:
https://doaj.org/article/0c9f9cd43550434fb45b1d354f4da122
Publikováno v:
Applied Sciences, Vol 11, Iss 18, p 8420 (2021)
Current ASR systems show poor performance in recognition of children’s speech in noisy environments because recognizers are typically trained with clean adults’ speech and therefore there are two mismatches between training and testing phases (i.
Externí odkaz:
https://doaj.org/article/fe822c2210854acd9cb678c765e87a47
Autor:
Maria Uther, Anna-Riikka Smolander, Katja Junttila, Mikko Kurimo, Reima Karhila, Seppo Enarvi, Sari Ylinen
Publikováno v:
Advances in Human-Computer Interaction, Vol 2018 (2018)
We investigated user experiences from 117 Finnish children aged between 8 and 12 years in a trial of an English language learning programme that used automatic speech recognition (ASR). We used measures that encompassed both affective reactions and q
Externí odkaz:
https://doaj.org/article/950aac4a70d44607bd1c2f27c68ef250
Publikováno v:
Lähikuva – audiovisuaalisen kulttuurin tieteellinen julkaisu. 35:57-69
Publikováno v:
Aalto University
In low resource children automatic speech recognition (ASR) the performance is degraded due to limited acoustic and speaker variability available in small datasets. In this paper, we propose a spectral warping based data augmentation method to captur
Publikováno v:
Linköping Electronic Conference Proceedings.
Publikováno v:
Language Resources and Evaluation.
Public sources like parliament meeting recordings and transcripts provide ever-growing material for the training and evaluation of automatic speech recognition (ASR) systems. In this paper, we publish and analyse the Finnish parliament ASR corpus, th