8th Annual Conference of the International Speech Communication Association

Antwerp, Belgium
August 27-31, 2007

Temporal Episodic Memory Model: An Evolution of Minerva2

Viktoria Maier, Roger K. Moore

University of Sheffield, UK

This paper introduces a new model for automatic speech recognition (ASR) called TEMM - Temporal Episodic Memory Model. TEMM is derived from a simulation of human episodic memory called Minerva2, and it not only overcomes the inability of Minerva2 to use temporal sequence for recognition flexibly, but it also employs a prediction mechanism as an additional source of information. The performance of TEMM on an ASR task is compared to state-of-the-art HMM/GMM baseline systems, and a first analysis shows both promising results and a need to further stabilise the consistency of the output of the new model.

Full Paper

Bibliographic reference.  Maier, Viktoria / Moore, Roger K. (2007): "Temporal episodic memory model: an evolution of minerva2", In INTERSPEECH-2007, 866-869.