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/).

Group members

Mikko Kurimo

Mikko Kurimo

Department of Signal Processing and Acoustics
Professor (Associate Professor)
Reima Karhila

Reima Karhila

Department of Signal Processing and Acoustics
Project Specialist
Stig-Arne Grönroos

Stig-Arne Grönroos

Department of Signal Processing and Acoustics
Doctoral Candidate

Katri Leino

Department of Signal Processing and Acoustics
Doctoral Candidate

Tuomas Kaseva

Department of Signal Processing and Acoustics
Research Assistant

Matias Lindgren

Department of Signal Processing and Acoustics
Research Assistant

Aku Rouhe

Department of Signal Processing and Acoustics
Doctoral Candidate

Anja Virkkunen

Department of Signal Processing and Acoustics
Doctoral Candidate

Juho Leinonen

Department of Signal Processing and Acoustics
Doctoral Candidate

Mittul Singh

Department of Signal Processing and Acoustics
Postdoctoral Researcher

Maria Sipilä

Department of Signal Processing and Acoustics
Project Specialist

Hemant Kathania

Department of Signal Processing and Acoustics
Postdoctoral Researcher

Tamás Grósz

Department of Signal Processing and Acoustics
Postdoctoral Researcher

Alexander Thorarinsson

Department of Signal Processing and Acoustics
Project Researcher

Emil Dewald

Department of Signal Processing and Acoustics
Project Employee

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

School common, ELEC, Department of Signal Processing and Acoustics, Speech Recognition, Centre of Excellence in Computational Inference, COIN

A user study to compare two conversational assistants designed for people with hearing impairments

Publishing year: 2019
Department of Signal Processing and Acoustics, Department of Neuroscience and Biomedical Engineering, Speech Recognition

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

Publishing year: 2019
Centre of Excellence in Computational Inference, COIN, School common, ELEC, Speech Recognition, Department of Signal Processing and Acoustics

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

Publishing year: 2019
Department of Signal Processing and Acoustics, Speech Recognition, Centre of Excellence in Computational Inference, COIN

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

Publishing year: 2019
Department of Signal Processing and Acoustics, Department of Neuroscience and Biomedical Engineering, Speech Recognition

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

Publishing year: 2019 MEMORY AND COGNITION
Department of Signal Processing and Acoustics, Department of Communications and Networking, Helsinki Institute for Information Technology HIIT, Centre of Excellence in Computational Inference, COIN, User Interfaces, Speech Recognition

Computer-Supported Form Design using Keystroke-Level Modeling with Reinforcement Learning

Publishing year: 2019
Department of Signal Processing and Acoustics, Helsinki Institute for Information Technology HIIT, Department of Communications and Networking, Centre of Excellence in Computational Inference, COIN, User Interfaces, Speech Recognition

RL-KLM: Automating Keystroke-level Modeling with Reinforcement Learning

Publishing year: 2019
Speech Recognition, Department of Signal Processing and Acoustics

Handling Noisy Labels for Robustly Learning from Self-Training Data for Low-Resource Sequence Labeling

Publishing year: 2019
Department of Signal Processing and Acoustics, Speech Recognition

Modern subword-based models for automatic speech recognition

Publishing year: 2019
Centre of Excellence in Computational Inference, COIN, School common, ELEC, Department of Signal Processing and Acoustics, Speech Recognition

The Aalto system based on fine-tuned AudioSet features for DCASE2018 task2 - general purpose audio tagging

Publishing year: 2018
More information on our research in the Research database.
Research database
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