Utilizing prosody for unconstrained morpheme recognition.
Speech recognition systems for languages with a rich inflectional morphology (like German) suffer from the limitations of a word-based full-form lexicon. Although the morphological and acoustical knowledge about words is coded implicitly within the lexicon entries (which are usually closely related to the orthography of the language at hand) this knowledge is usually not explicitly available for other tasks (e.g. detecting OOV words, prosodic analysis). This paper presents an HMM-based `word' recognizer that uses morpheme-like units on the string level for recognizing spontaneous German conversational speech (Verbmobil corpus). The system has no explicit word knowledge but uses a morpheme-bigram to capture the German word and sentence structure to some extent. The morpheme recognizer is tightly coupled with a prosodic classifier in order to compensate for some of the additional ambiguity introduced by using morphemes instead of words.