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.

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,

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

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

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

Multi-task wav2vec2 Serving as a Pronunciation Training System for Children

Yaroslav Getman, Ragheb Al-Ghezi, Tamas Grosz, Mikko Kurimo 2023 9th Workshop on Speech and Language Technology in Education (SLaTE)

Investigating wav2vec2 context representations and the effects of fine-tuning, a case-study of a Finnish model

Tamas Grosz, Yaroslav Getman, Ragheb Al-Ghezi, Aku Rouhe, Mikko Kurimo 2023 Proceedings of Interspeech 2023

Non-game like training benefits spoken foreign-language processing in children with dyslexia

Katja Junttila, Anna Riikka Smolander, Reima Karhila, Mikko Kurimo, Sari Ylinen 2023 FRONTIERS IN HUMAN NEUROSCIENCE

Multilingual TTS Accent Impressions for Accented ASR

Georgios Karakasidis, Nathaniel Robinson, Yaroslav Getman, Atieno Ogayo, Ragheb Al-Ghezi, Ananya Ayasi, Shinji Watanabe, David R. Mortensen, Mikko Kurimo 2023 Text, Speech, and Dialogue - 26th International Conference, TSD 2023, Proceedings

A pronunciation Scoring System Embedded into Children’s Foreign Language Learning Games with Experimental Verification of Learning Benefits

Reima Karhila, Sari Ylinen, Anna-Riikka Smolander, Aku Rouhe, Ragheb Al-Ghezi, Yaroslav Getman, Tamas Grosz, Maria Uther, Mikko Kurimo 2023 9th Workshop on Speech and Language Technology in Education (SLaTE)

Spectral warping based data augmentation for low resource children’s speaker verification

Hemant Kumar Kathania, Virender Kadyan, Sudarsana Reddy Kadiri, Mikko Kurimo 2023 Multimedia Tools and Applications

New data, benchmark and baseline for L2 speaking assessment for low-resource languages

Mikko Kurimo, Yaroslav Getman, Ekaterina Voskoboinik, Ragheb Al-Ghezi, Heini Kallio, Mikko Kuronen, Anna von Zansen, Raili Hilden, Sirkku Kronholm, Ari Huhta, Krister Lindén 2023 Proceedings of 9th Workshop on Speech and Language Technology in Education (SLaTE)

Evaluating Morphological Generalisation in Machine Translation by Distribution-Based Compositionality Assessment

Anssi Moisio, Mathias Creutz, Mikko Kurimo 2023 Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)
More information on our research in the Aalto research portal.
Research portal
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