The prosodic structure of speech is based on complex interaction within and between several different levels of linguistic, and paralinguistic organization, and is expressed in the modulation of F0, intensity, duration, and voice quality, as well as the occurrence of pauses. Even though leading theories of prosody maintain that prosody is shaped through the interaction of grammatical factors fr...

Speech parameters originating from voice source and vocal tract were analyzed to find acoustic correlates of dimensional descriptions of emotional states. To achieve this goal best, we adopted the Utsunomiya University Spoken Dialogue Database, which was designed for studies on paralinguistic information in expressive conversational speech. Analyses for four female and two male speakers showed:...

We describe a “direct modeling” approach to using prosody in various speech technology tasks. The approach does not involve any hand-labeling or modeling of prosodic events such as pitch accents or boundary tones. Instead, prosodic features are extracted directly from the speech signal and from the output of an automatic speech recognizer. Machine learning techniques then determine a prosodic m...

The Prosodic Module of SLIM has been created in order to solve problems related to segmental and suprasegmental features of spoken English in a courseware for computerassisted foreign language learning called SLIM an acronym for Multimedia Interactive Linguistic Software, developed at the University of Venice. It is composed of two different sets of Learning Activities, the first one dealing wi...

Paralinguistic cues in children’s speech convey the child’s affective state and can serve as important markers for the early detection of autism spectrum disorder (ASD). In this paper, we detect paralinguistic events, such as laughter and fussing/crying, along with toddlers’ speech from the Multi-modal Dyadic Behavior Dataset (MMDB). We use both spectral and prosodic acoustic features selected ...

In conventional concept-to-speech (CTS) methods, a common step is predicting abstract prosodic descriptions, such as the locations of accents and phrase boundaries, from the linguistic information provided by the text generation module. But the prediction results always contain errors, and unacceptable prosodic prediction may ruin the synthesized speech. In addition, linguistic information, whi...

This contribution describes a method for the automatic prosodic labeling of multi-lingual speech data. The prosodic labels are word boundary strength and word prominence. The speech signal and its orthographic representation are first transformed to feature vectors comprising acoustic and linguistic features such as pitch, duration, energy, part-of-speech, punctuation, word frequency and stress...

Call Centre data is typically collected by organizations and corporations in order to ensure the quality of service, supporting for example mining capabilities for monitoring customer satisfaction. In this work, we analyze the significance of various acoustic features extracted from customer-agents’ spoken interaction in predicting self-reported satisfaction by the customer. We also investigate...

Natural language processing (NLP) is gradually becoming a more multidisciplinary field, and research in remotely connected aspects of language such as paralinguistic phonetics may benefit from as well as contribute to some areas of NLP. This paper provides a brief overview of paralinguistic phonetics, and some current NLPrelated methods and models used in TTS and ASR systems today. In order to ...

The basic goal of the voice conversion system to mimics the characteristics of the target speaker voice by keeping the linguistic and paralinguistic information intact. The characteristics of a speaker in speech reflect at different level such as vocal tract, excitation and prosodic parameters. This propose work based on cepstrum which represents the vocal tract and excitation parameters of the...