Skip to content
Master's Thesis
TeX Max MATLAB Python
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
latex
matlab
src
README.md
mst_lukkarila_juri_2017.pdf

README.md

Master's Thesis

Developing a Conversation Assistant for the Hearing Impaired Using Automatic Speech Recognition

Aalto University School of Electrical Engineering,
Department of Signal Processing and Acoustics,
2017

Advisor: D.Sc. Kalle Palomäki

Aalto publication archive

Abstract:

Understanding and participating in conversations has been reported as one of the biggest challenges hearing impaired people face in their daily lives. These communication problems have been shown to have wide-ranging negative consequences, affecting their quality of life and the opportunities available to them in education and employment.

A conversational assistance application was investigated to alleviate these problems. The application uses automatic speech recognition technology to provide real-time speech-to-text transcriptions to the user, with the goal of helping deaf and hard of hearing persons in conversational situations. To validate the method and investigate its usefulness, a prototype application was developed for testing purposes using open-source software. A user test was designed and performed with test participants representing the target user group.

The results indicate that the Conversation Assistant method is valid, meaning it can help the hearing impaired to follow and participate in conversational situations. Speech recognition accuracy, especially in noisy environments, was identified as the primary target for further development for increased usefulness of the application. Conversely, recognition speed was deemed to be sufficient and already surpass the transcription speed of human transcribers.

You can’t perform that action at this time.