Ulrich Kordon

A multilingual TTS system with less than 1 Mbyte footprint for embedded applications

Text-to-speech (TTS) systems have improved their quality to a large extent lately. This development has resulted in memory requirements of several megabytes that cannot be accepted in many applications, especially in embedded systems. Such applications are usually limited to a footprint of as much as 1 megabyte and require the processing power to be as low as possible. These requirements may be met if the text processing is changed from the usual data-driven algorithms to rule-based processing. Furthermore, the inventory (diphone inventory) should be as small as possible and should be stored in a compressed manner. This is demonstrated by a modified version of the Dresden speech synthesis system, DRESS, which is called microDRESS. Compared to the baseline system, microDRESS does not show essential quality losses apart from the influences of the telephone bandwidth which is appropriate for many embedded applications.

Auscultatory Blood Pressure Measurement using HMMs

This paper reports on a study of applying an HMM-based labeler along with a tailored feature extraction to Korotkoff sounds. These sounds can be heard through a stethoscope during the auscultatory blood pressure measurement usually done at medical practices. While this method works well when the patient is at rest, interfering noise from muscles and joints cause major problems when the subject is doing any activities like sports or fitness exercises. We propose a signal processing and classification method to overcome these difficulties and present first promising results.