Synthesizing speech from speech recognition parameters

The merits of different signal preprocessing schemes for speech recognizers are usually assessed purely on the basis of the resulting recognition accuracy. Such benchmarks give a good indication as to whether one preprocessing is better than another, but little knowledge is acquired about why it is better or how it could be further improved. In order to gain more insight in the preprocessing, we seek to re-synthesize speech from speech recognition features. This way, we are able to pin-point some deficiencies in our current preprocessing scheme. Additional analysis of successful new preprocessing schemes may allow us one day to identify precisely those properties that are desirable in a feature set. Next to these purely scientific aims, the re-synthesis of speech from recognition features is of interest to thin-client speech applications, and as an alternative to the classical LPC source-filter model for speech manipulation.