Andreas Kießling

Prosodic scoring of word hypotheses graphs

Prosodic boundary detection is important to disam biguate parsing especially in spontaneous speech where elliptic sentences occur frequently Word graphs are an e cient interface between word recognition and parser Prosodic classi cation of word chains has been published earlier The adjustments necessary for applying these classi cation techniques to word graphs are discussed in this paper When classifying a word hypothesis a set of context words has to be determined appropriately A method has been developed to use stochastic language models for prosodic classi cation This as well has been adopted for the use on word graphs We also improved the set of acoustic prosodic features with which the recog nition errors were reduced by about on the read speech we were working on previously now achieving error rate for boundary classes and for accent classes Moving to spontaneous speech the recognition er ror increases signi cantly e g for a class boundary task We show that even on word graphs the combina tion of language models which model a larger context with acoustic prosodic classi ers reduces the recognition error by up to

MÜSLI: A Classification Scheme For Laryngealizations

We developed a classification scheme for laryngealizations that can be used to discriminate the many different shapes of laryngealizations with different feature values. Potential applications are phonetic transcription and automatic detection. The scheme was developed and tested with a database from 4 speakers that contains more than 1200 laryngealizations.

Filled pauses in spontaneous speech

Filled pauses as e g uh eh signal dis uencies i e hesitations or repairs They do normally not occur in read speech and were therefore up to now rather seldom investigated they must however be ac counted for in the automatic processing of spontaneous speech We present de scriptive statistics and the results of an au tomatic classi cation of lled pauses in the database of the VERBMOBIL project and discuss the relevancy of di erent prosodic features for the marking of di erent types

Integrating syntactic and prosodic information for the efficient detection of empty categories

We describe a number of experiments that demonstrate the usefulness of prosodic information for a processing module which parses spoken utterances with a feature-based grammar employing empty categories. We show that by requiring certain prosodic properties from those positions in the input, where the presence of an empty category has to be hypothesized, a derivation can be accomplished more efficiently. The approach has been implemented in the machine translation project VERBMOBIL and results in a significant reduction of the work-load for the parser.

Why sentence modality in spontaneous speech is more difficult to classify and why this fact is not too bad for prosody

We show in this paper that the labeling of sentence modality in German, esp. of questions vs. non-questions, is more difficult for spontaneous than for read speech and easier for non-elliptic than for elliptic utterances. However, the prosodic marking of sentence modality is more important in elliptic utterances that occur more often in spontaneous speech.

Prosody takes over: towards a prosodically guided dialog system

Abstract The domain of the speech recognition and dialog system EVAR is train time table inquiry. We observed that in real human-human dialogs when the officer transmits the information, the customer very often interrupts. Many of these interruptions are just repetitions of the time of day given by the officer. The functional role of these interruptions is often determined by prosodic cues only. An important result of experiments where naive persons used the EVAR system is that it is hard to follow the train connection given via speech synthesis. In this case it is even more important than in human-human dialogs that the user has the opportunity to interact during the answer phase. Therefore we extended the dialog module to allow the user to repeat the time of day and we added a prosody module guiding the continuation of the dialog by analyzing the intonation contour of this utterance.

Prosodic Modules for Speech Recognition and Understanding in VERBMOBIL

Within VERBMOBIL, a large project on spoken language research in Germany, two modules for detecting and recognizing prosodic events have been developed. One module operates on speech signal parameters and the word hypothesis graph, whereas the other module, designed for a novel, highly interactive architecture, only uses speech signal parameters as its input. Phrase boundaries, sentence modality, and accents are detected. The recognition rates in spontaneous dialogs are for accents up to 82.5%, for phrase boundaries up to 91.7%.

Prosody takes over : a prosodically guided dialog system

In this paper first experiments with naive persons using the speech understanding and dialog system EVAR are discussed. The domain of EVAR is train table inquiry. We observed that in real human-human dialogs when the officer transmits the information the customer very often interrupts. Many of these interruptions are just repetitions of the time of day given by the officer. The functional role of these interruptions is determined by prosodic cues only. An important result of the experiments with EVAR is that it is hard to follow the system giving the train connection via speech synthesis. In this case it is even more important than in human-human dialogs that the user has the opportunity to interact during the answer phase. Therefore we extended the dialog module to allow the user to repeat the time of day and we added a prosody module guiding the continuation of the dialog.

Detection of phrase boundaries and accents

On a large speech database read by untrained speakers experiments for the recognition of phrase boundaries and phrase accents were performed. We used durational features as well as features derived from pitch and energy contours and pause information. Different sets of features were compared. For distinguishing three different boundary classes a recognition rate of 75.7% and for distinguishing accentuated from unaccentuated syllables a recognition rate of 88.7% could be achieved.

Classification of boundaries and accents in spontaneous speech

Das diesem Bericht zugrundeliegende Forschungsvorhaben wurde mit Mitteln des Bundesministers f ur Bildung, Wissenschaft, Forschung und Technologie unter dem F orderkennzeichen 01 IV 102 H/0 und 01 IV 102 F/4 gef ordert. Die Verantwortung f ur den Inhalt dieser Arbeit liegt bei den Autoren.