Department of Signal Processing and Acoustics

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.
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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/).

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

Gaming enhances learning-induced plastic changes in the brain

Katja Junttila, Anna Riikka Smolander, Reima Karhila, Anastasia Giannakopoulou, Maria Uther, Mikko Kurimo, Sari Ylinen 2022 Brain and Language

A Formant Modification Method for Improved ASR of Children’s Speech

Hemant Kathania, Sudarsana Kadiri, Paavo Alku, Mikko Kurimo 2022 Speech Communication

Lahjoita puhetta: a large-scale corpus of spoken Finnish with some benchmarks

Anssi Moisio, Dejan Porjazovski, Aku Rouhe, Yaroslav Getman, Anja Virkkunen, Ragheb AlGhezi, Mietta Lennes, Tamás Grósz, Krister Lindén, Mikko Kurimo 2022 LANGUAGE RESOURCES AND EVALUATION

Self-supervised end-to-end ASR for low resource L2 Swedish

Ragheb Al-Ghezi, Yaroslav Getman, Aku Rouhe, Raili Hildén, Mikko Kurimo 2021 22nd Annual Conference of the International Speech Communication Association, INTERSPEECH 2021

LSTM-XL: Attention Enhanced Long-Term Memory for LSTM Cells

Tamás Grósz, Mikko Kurimo 2021 Text, Speech, and Dialogue - 24th International Conference, TSD 2021, Proceedings

Synthesis Speech Based Data Augmentation for Low Resource Children ASR

Virender Kadyan, Hemant Kathania, Prajjval Govil, Mikko Kurimo 2021 Speech and Computer - 23rd International Conference, SPECOM 2021, Proceedings

Speaker Verification Experiments for Adults and Children Using Shared Embedding Spaces

Tuomas Kaseva, Hemant Kathania, Aku Rouhe, Mikko Kurimo 2021 Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa), May 31-June 2, 2021

Spectral modification for recognition of children’s speech under mismatched conditions

Hemant Kathania, Sudarsana Kadiri, Paavo Alku, Mikko Kurimo 2021 Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)

Using data augmentation and time-scale modification to improve ASR of children’s speech in noisy environments

Hemant Kathania, Sudarsana Kadiri, Paavo Alku, Mikko Kurimo 2021 APPLIED SCIENCES

Vowel non-vowel based spectral warping and time scale modification for improvement in children’s ASR

Hemant Kathania, Avinash Kumar, Mikko Kurimo 2021 IEEE International Conference on Acoustics, Speech and Signal Processing
More information on our research in the Research database.
Research database
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