Student Project Assistant: Manual Prosodic Annotation of Conversational German

Automatic speech recognition (ASR) systems were originally designed to cope with carefully pronounced speech. Most real world applications of ASR systems, however, require the recognition of spontaneous, conversational speech (e.g., dialogue systems, voice input aids for physically disabled, medical dictation systems, etc.). Compared to prepared speech, conversational speech contains utterances that might be considered 'ungrammatical' and contain disfluencies such as “...oh, well, I think ahm exactly …”. Moreover, in spontaneous conversation, a word like “yesterday” may sound like yeshay and the German word “haben” (“to have”) may sound like ham. The pronunciation of the words depends on well-known factors, for instance on the regional background of the speakers and the formality of the situation. Highly influential, but not so well studied factors are those reflecting the prosodic characteristics of the word in the utterance. These prosodic characteristics describe the rhythm and melody of a sentence, and for instance, whether a word is accented or not.

In order to analyze prosodic characteristics, a large amount of annotated material is necessary. For this purpose, we need a phonetically trained student, who will create manual prosodic annotations of Austrian German conversations. The candidate should speak German fluently, have a background in linguistics and phonetics and should have previously worked with PRAAT or a similar speech processing software (e.g.,  ELAN, STX). A background in prosody is especially welcome. Furthermore, it is possible to combine this practical work with writing a Bachelor or Master thesis on a prosody related topic (in the fields of linguistics or speech technology).

Student Assistants can be hired from November 2018 onwards for up to one year for approximately 10 to 15 hours per week. Annotations can be made at home or at our laboratory. Please send your application letter and your CV to



12. November 2018 - 30. June 2019
Prof. Dr. Margaret Zellers
Prof. Dina El Zarka