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
A transformer-based spelling error correction framework for Bangla and resource scarce Indic languages
Mehedi Hasan Bijoy, Nahid Hossain, Salekul Islam, Swakkhar Shatabda
2025
Computer Speech and Language
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
CaptainA self-study mobile app for practising speaking: task completion assessment and feedback with generative AI
Nhan Phan Chi, Anna von Zansen, Maria Kautonen, Tamás Grósz, Mikko Kurimo
2024
Comparison and analysis of new curriculum criteria for end-to-end ASR
Georgios Karakasidis, Mikko Kurimo, Peter Bell, Tamás Grósz
2024
Speech Communication
LLMs’ morphological analyses of complex FST-generated Finnish words
Anssi Moisio, Mathias Creutz, Mikko Kurimo
2024
CMCL 2024 - 13th Edition of the Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop
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
Automated content assessment and feedback for Finnish L2 learners in a picture description speaking task
Nhan Phan, Anna von Zansen, Maria Kautonen, Ekaterina Voskoboinik, Tamas Grosz, Raili Hilden, Mikko Kurimo
2024
Proceedings of the Interspeech 2024
From Raw Speech to Fixed Representations: A Comprehensive Evaluation of Speech Embedding Techniques
Dejan Porjazovski, Tamas Grosz, Mikko Kurimo
2024
IEEE/ACM Transactions on Audio Speech and Language Processing
Improved Spoken Emotion Recognition With Combined Segment-Based Processing And Triplet Loss
Dejan Porjazovski, Tamás Grósz, Mikko Kurimo
2024
Proceedings of the 7th International Conference on Natural Language and Speech Processing (ICNLSP 2024)
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