Speech Recognition Supported by Prosodic Information for Fixed Stress Languages

In our paper we examine the usage of prosodic features in speech recognition, with a special attention payed to agglutinating and fixed stress languages. The used prosodic features, acoustic-prosodic preprocessing, and segmentation in terms of prosodic units are presented in details. We use the expression ”prosodic unit” in order to make a difference from prosodic phrases, which are longer. We trained a HMM-based prosodic segmenter reliing on fundamental frequency and intensity of speech. The output of the prosodic segmenter is used for N-best lattice rescoring in parallel with a simplified bigram language model in a continuous speech recognizer, in order to improve speech recognition performance. Experiments for Hungarian language show a WER reduction of about 4% using a simple lattice rescoring.