Projects:2015s1-05 Multi-Profile Parallel Transcriber

Team

Students

• Dakshitha Narendra Kirana Kankanamage

• Siyuan Ma

Supervisors

• Dr. Said Al-Sarawi
• Dr. Ahmad Hashemi-Sakhtsari

Introduction

The field of Automatic Speech Recognition (ASR) has been a major field of interest for researchers over the past few decades. Although, it was strongly believed to play a major role in Human-Machine as well as Human-Human interactions [1] [2] [3], the real world users have been unable to utilize this due to the slow pace of advancements in the field. Today, with the rise of portable electronic devices and more powerful computers, Speech Recognition (SR) technology has experienced a great push forward, thereby providing the everyday user a better Human-Machine experience and researchers the power to overcome obstacles that could not have been done so before.

Aims

The aims of this project are to:

1. Set up a working copy of the Multi Profile Transcriber on the provided computer and review its functional integrity.
2. Set up evaluation standards and evaluate the current state of the system.
3. Upgrade the software to contain the latest version of the embedded speech engine.
4. Re-run the evaluation phase on the upgraded system.
5. Extend its functionality.
6. Re-run the evaluation phase on the extended system.

References

[1] L. D. Dong Yu, Automatic Speech Recognition: A Deep Learning Approach, 1 ed. London: Springer London, 2015.

[2] P. M. Kitzing, A ; Ahlander, Vl, "Automatic speech recognition (ASR) and its use as a tool for assessment or therapy of voice, speech, and language disorders," Logopedics Phoniatrics Vocology, vol. 34, pp. 91-96, 2009.

[3] X. H. a. L. Deng, "An Overview of Modern Speech Recognition," in Handbook of Natural Language Processing, Second Edition, N. I. a. F. J. Damerau, Ed., ed Boca Raton, FL: Chapman & Hall/CRC, 2010.