We investigate the usefulness of DISfluencies and Non-verbal Vocalisations (DIS-NV) for recognizing human emotions in dialogues. The proposed features measure filled pauses, fillers, stutters, laughter, and breath in utterances. The predictiveness of DISNV features is compared with lexical features and state-of-the-art low-level acoustic features. Our experimental results show that using DIS-NV...

Structural events, (i.e., the structure of clauses and disfluencies) in spontaneous speech, are important components of human speaking and have been used to measure language development. However, they have not been actively used in automated speech assessment research. Given the recent substantial progress on automated structural event detection on spontaneous speech, we investigated the detect...

The paper introduces our strategy for adapting a rule based parser of written language to transcribed speech. Special attention has been paid to disfluencies (repairs, repetitions and false starts). A Constraint Grammar based parser was used for shallow syntactic analysis of spoken Estonian. The modification of grammar and additional methods improved the recall from 97.5% to 97.7% and precision...

We investigate the usefulness of DISfluencies and Non-verbal Vocalisations (DIS-NV) for recognizing human emotions in dialogues. The proposed features measure filled pauses, fillers, stutters, laughter, and breath in utterances. The predictiveness of DISNV features is compared with lexical features and state-of-the-art low-level acoustic features. Our experimental results show that using DIS-NV...

Compared to dictation systems, recognition systems for spontaneous speech still perform rather poorly. An important weakness in these systems is the statistical language model, mainly due to the lack of large amounts of stylistically matching training data and to the occurrence of disfluencies in the recognition input. In this paper we investigate a method for improving the robustness of a spon...

Hesitations, interruptions within phrases or within words are common in spontaneous speech. Those phenomena are widely known to be observable from a prosodic point of view through disfluencies. From a syntactic point of view, many studies already established that discursive markers such as hm, oh, I mean, etc. are representative of spontaneous speech. In this study, we demonstrate through a joi...

Unlike rehearsed and prepared speech, spontaneous speech contains high occurrence of disfluencies, like repetitions, filled pauses, and hesitations. Disfluencies can seriously hamper the word recognition accuracy of an Automatic Speech Recogniser (ASR), by increasing word insertion and deletion and rejection rates. In this paper we introduce signal processing algorithms to automatically identif...

We discuss perception studies of two low level indicators of discourse phenomena by Swedish, Japanese, and Chinese native speakers. Subjects were asked to identify upcoming prosodic boundaries and disfluencies in Swedish spontaneous speech. We hypothesize that speakers of prosodically unrelated languages should be less able to predict upcoming phrase boundaries but potentially better able to id...

Parsing disfluent sentences is a challenging task which involves detecting disfluencies as well as identifying the syntactic structure of the sentence. While there have been several studies recently into solely detecting disfluencies at a high performance level, there has been relatively little work into joint parsing and disfluency detection that has reached that state-ofthe-art performance in...