1 code implementation • 22 Feb 2024 • Daniel Holmberg, Manu Airaksinen, Viviana Marchi, Andrea Guzzetta, Anna Kivi, Leena Haataja, Sampsa Vanhatalo, Teemu Roos
Reliable methods for the neurodevelopmental assessment of infants are essential for early detection of medical issues that may need prompt interventions.
1 code implementation • 16 May 2023 • Einari Vaaras, Manu Airaksinen, Sampsa Vanhatalo, Okko Räsänen
The recently-developed infant wearable MAIJU provides a means to automatically evaluate infants' motor performance in an objective and scalable manner in out-of-hospital settings.
1 code implementation • 21 Jun 2022 • Einari Vaaras, Manu Airaksinen, Okko Räsänen
In this paper, we combine CPC and multiple dimensionality reduction methods in search of functioning practices for clustering-based AL. Our experiments for simulating speech emotion recognition system deployment show that both the local and global topology of the feature space can be successfully used for AL, and that CPC can be used to improve clustering-based AL performance over traditional signal features.
no code implementations • 2 Jul 2021 • Manu Airaksinen, Sampsa Vanhatalo, Okko Räsänen
In addition, we explore the benefits of data augmentation methods in ideal and non-ideal recording conditions.
no code implementations • 21 Sep 2019 • Manu Airaksinen, Okko Räsänen, Elina Ilén, Taru Häyrinen, Anna Kivi, Viviana Marchi, Anastasia Gallen, Sonja Blom, Anni Varhe, Nico Kaartinen, Leena Haataja, Sampsa Vanhatalo
These data were manually annotated for infant posture and movement based on video recordings of the sessions, and using a novel annotation scheme specifically designed to assess the overall movement pattern of infants in the given age group.
no code implementations • 25 Apr 2018 • Lauri Juvela, Vassilis Tsiaras, Bajibabu Bollepalli, Manu Airaksinen, Junichi Yamagishi, Paavo Alku
Recent speech technology research has seen a growing interest in using WaveNets as statistical vocoders, i. e., generating speech waveforms from acoustic features.
1 code implementation • 3 Apr 2018 • Lauri Juvela, Bajibabu Bollepalli, Xin Wang, Hirokazu Kameoka, Manu Airaksinen, Junichi Yamagishi, Paavo Alku
This paper proposes a method for generating speech from filterbank mel frequency cepstral coefficients (MFCC), which are widely used in speech applications, such as ASR, but are generally considered unusable for speech synthesis.