Adaption of ASR for Impaired Speech with minimum resources (AdAIS)

This micro project will study the adaptation of automatic speech recognition (ASR) systems for impaired speech. Specifically, the micro-project will focus on improving ASR systems for speech from subjects with dysarthria and/or stuttering speech impairment types of various degrees. The work will be developed using either German “Lautarchive” data comprising only 130 hours of untranscribed doctor-patient German speech conversations and/or using English TORGO dataset. Applying human-in-the-loop methods we will spot individual errors and regions of low certainty in ASR in order to apply human-originated improvement and clarification in AI decision processes.

Output

Paper for ICASSP 2021 and/or Interspeech 2022

Presentations

Project Partners:

• Brno U, Mireia Diez
• Technische Universität Berlin (TUB), Tim Polzehl

Primary Contact: Mireia Diez Sanchez, Brno University of Technology

Main results of micro project:

Project has run for less than 50% of its allocated time.

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Contribution to the objectives of HumaneAI-net WPs

WP1 Learning, Reasoning and Planning with Human in the Loop
T1.1 Linking symbolic and subsymbolic learning

WP3 Human AI Interaction and Collaboration
T3.1 Foundations of Human-AI interaction and Collaboration
T3.6 Language-based and multilingual interaction
T3.7 Conversational, Collaborative AI

WP6 Applied research with industrial and societal use cases
T6.3 Software platforms and frameworks
T6.5 Health related research agenda and industrial usecases

Tangible outputs

• Publication: –
• Other: Internal report – Mireia Diez Sanchez, mireia@fit.vutbr.cz