Speech recognition
Our goal is to generally improve the speech recognition methodology with the help of the new algorithms developed in Aalto University. Speech recognition offers challenging benchmarking tasks for efficient algorithms that can process and learn to represent large quantities of data. In addition to improving the acoustic models of phonemes we aim at developing new learning statistical language models for difficult large vocabulary continuous speech recognition tasks.
Research Overview
We currently specialize in the following research areas in speech recognition:
- Sub-word units and deep learning in language modeling
- Speaker adaptation and pronunciation rating in acoustic modeling
- Unlimited vocabulary continuous speech recognition
- Speech recognition and language modeling methods for under-resourced languages
- Methods for describing and translating audiovisual
- Speaker and language recognition and diarization
We are part of Finnish Center of Artificial Intelligence (FCAI, https://fcai.fi/).
Teaching
We are teaching the following courses:
ELEC-E5550 Statistical Natural Language Processing
Group members
Software & Demonstrations
Software produced as part of our research is available on our GitHub
Demonstration videos of our research work can be watched on our YouTube Channel
Latest publications
Use of Self-Supervised Learning in Automated Speaking Scoring for Low Resource Languages
Ragheb Al-Ghezi
2024
Towards Sustainable Agriculture : A Novel Approach for Rice Leaf Disease Detection Using dCNN and Enhanced Dataset
Mehedi Hasan Bijoy, Nirob Hasan, Mithun Biswas, Suvodeep Mazumdar, Andrea Jimenez, Faisal Ahmed, Mirza Rasheduzzaman, Sifat Momen
2024
IEEE Access
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, Yaroslav Getman, Támas Grosz, Xinwei Cao, Torbjørn Svendsen, Giampiero Salvi
2024
2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Main Conference Proceedings
Attention-based End-to-End Models in Language Technology
Aku Rouhe
2024
Principled Comparisons for End-to-End Speech Recognition: Attention vs Hybrid at the 1000-hour Scale
Aku Rouhe, Tamás Grósz, Mikko Kurimo
2024
IEEE/ACM Transactions on Audio, Speech, and Language Processing
Listening like a speech-training app: Expert and non-expert listeners’ goodness ratings of children’s speech
Sofia Strömbergsson, Molly Fröjdh, Magdalena Pettersson, Tamás Grósz, Yaroslav Getman, Mikko Kurimo
2024
Clinical Linguistics and Phonetics
INVESTIGATING THE CLUSTERS DISCOVERED BY PRE-TRAINED AV-HUBERT
Anja Virkkunen, Guangpu Huang, Tamas Grosz, Mikko Kurimo
2024
2024 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024 - Proceedings
Automatic Rating of Spontaneous Speech for Low-Resource Languages
Ragheb Al-Ghezi, Yaroslav Getman, Ekaterina Voskoboinik, Mittul Singh, Mikko Kurimo
2023
2022 IEEE Spoken Language Technology Workshop, SLT 2022 - Proceedings
Automatic Speaking Assessment of Spontaneous L2 Finnish and Swedish
Ragheb Al-Ghezi, Ekaterina Voskoboinik, Yaroslav Getman, Anna Von Zansen, Heini Kallio, Mikko Kurimo, Ari Huhta, Raili Hildén
2023
Language Assessment Quarterly
Developing an AI-assisted Low-resource Spoken Language Learning App for Children
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
2023
IEEE Access
- Published:
- Updated: