Temporal Difference Learning Applied to Continuous Speech Recognition

This paper evaluates the performance of two reinforcement learning algorithms on four, increasingly complex tasks of continuous speech recognition. Simulations reveal that when errors are examined only at word boundaries, both algorithms provide performance comparable with that of a fully supervised system.