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

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)


Hemant Kathania, Avinash Kumar, Mikko Kurimo 2021 IEEE International Conference on Acoustics, Speech and Signal Processing

Attention-Based End-To-End Named Entity Recognition From Speech

Dejan Porjazovski, Juho Leinonen, Mikko Kurimo 2021 Text, Speech, and Dialogue

Advances in subword-based HMM-DNN speech recognition across languages

Peter Smit, Sami Virpioja, Mikko Kurimo 2021 Computer Speech and Language

Morphologically motivated word classes for very large vocabulary speech recognition of Finnish and Estonian

Matti Varjokallio, Sami Virpioja, Mikko Kurimo 2021 Computer Speech and Language

The Effects of a Digital Articulatory Game on the Ability to Perceive Speech-Sound Contrasts in Another Language

Sari Ylinen, Anna Riikka Smolander, Reima Karhila, Sofoklis Kakouros, Jari Lipsanen, Minna Huotilainen, Mikko Kurimo 2021 Frontiers in Education

Graph-based Syntactic Word Embeddings

Ragheb Al-Ghezi, Mikko Kurimo 2020 Proceedings of the Graph-based Methods for Natural Language Processing (TextGraphs)

Applying dnn adaptation to reduce the session dependency of ultrasound tongue imaging-based silent speech interfaces

Gábor Gosztolya, Tamás Grósz, László Tóth, Alexandra Markó, Tamás Gábor Csapó 2020 ACTA POLYTECHNICA HUNGARICA
More information on our research in the Research database.
Research database
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