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

Mikko Kurimo

Professori (Associate professor)
[email protected]
+358503476221

Katri Leino

Tohtorikoulutettava
[email protected]

Aku Rouhe

Doctoral candidate
[email protected]

Anja Virkkunen

Tohtorikoulutettava
[email protected]

Juho Leinonen

Tohtorikoulutettava
[email protected]

Mittul Singh

Tutkijatohtori
[email protected]
+358505147551

Hemant Kathania

Postdoctoral researcher
[email protected]
+358503420092

Tamás Grósz

Postdoctoral researcher
[email protected]

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

Visual Interpretation of DNN-based Acoustic Models using Deep Autoencoders

Tamás Grósz, Mikko Kurimo 2020 Machine Learning Methods in Visualisation for Big Data

Study of Formant Modification for Children ASR

Hemant Kathania, Sudarsana Kadiri, Paavo Alku, Mikko Kurimo 2020 Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing

Brain activity reflects the predictability of word sequences in listened continuous speech

Miika Koskinen, Mikko Kurimo, Joachim Gross, Aapo Hyvärinen, Riitta Hari 2020 NeuroImage

Creating speaker independent ASR system through prosody modification based data augmentation

S. Shahnawazuddin, Nagaraj Adiga, Hemant Kumar Kathania, B. Tarun Sai 2020 Pattern Recognition Letters

Effects of Language Relatedness for Cross-lingual Transfer Learning in Character-Based Language Models

Mittul Singh, Peter Smit, Sami Virpioja, Mikko Kurimo 2020 Proceedings of the 1st Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL)

North Sámi morphological segmentation with low-resource semi-supervised sequence labeling

Stig-Arne Grönroos, Sami Virpioja, Mikko Kurimo 2019 Fifth Workshop on Computational Linguistics for Uralic Languages

Building personalised speech technology systems with sparse, bad quality or out-of-domain data

Reima Karhila 2019

Transparent pronunciation scoring using articulatorily weighted phoneme edit distance

Reima Karhila, Anna Riikka Smolander, Sari Ylinen, Mikko Kurimo 2019 Proceedings of Interspeech

Spherediar: An Effective Speaker Diarization System for Meeting Data

Tuomas Kaseva, Aku Rouhe, Mikko Kurimo 2019 2019 IEEE Automatic Speech Recognition and Understanding Workshop, ASRU 2019 - Proceedings

Statistical models of morphology predict eye-tracking measures during visual word recognition

Minna Lehtonen, Matti Varjokallio, Henna Kivikari, Annika Hultén, Sami Virpioja, Tero Hakala, Mikko Kurimo, Krista Lagus, Riitta Salmelin 2019 MEMORY AND COGNITION
More information on our research in the Research database.
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