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Speech and Human-Machine Dialog focuses on the dialog management component of a spoken language dialog system. Spoken language dialog systems provide a natural interface between humans and computers. These systems are of special interest for interactive applications, and they integrate several technologies including speech recognition, natural language understanding, dialog management and speech synthesis.

Due to the conjunction of several factors throughout the past few years, humans are significantly changing their behavior vis-a-vis machines. In particular, the...

In Monitoring Adaptive Spoken Dialog Systems, authors Alexander Schmitt and Wolfgang Minker investigate statistical approaches that allow for recognition of negative dialog patterns in Spoken Dialog Systems (SDS). The presented stochastic methods allow a flexible, portable and accurate use.

Beginning with the foundations of machine learning and pattern recognition, this monograph examines how frequently users show negative emotions in spoken dialog systems and develop novel approaches to speech-based emotion recognition using hybrid approach to model emotions. The authors make...

In Monitoring Adaptive Spoken Dialog Systems, authors Alexander Schmitt and Wolfgang Minker investigate statistical approaches that allow for recognition of negative dialog patterns in Spoken Dialog Systems (SDS). The presented stochastic methods allow a flexible, portable and accurate use.
Beginning with the foundations of machine learning and pattern recognition, this monographexamines how frequently users show negative emotions in spoken dialog systems and develop novel approaches to speech-based emotion recognition using hybrid approach to model emotions. The authors make...

Bandwidth Extension of Speech Signals describes the theory and methods for quality enhancement of clean speech signals and distorted speech signals such as those that have undergone a band limitation, for instance, in a telephone network. Problems and the respective solutions are discussed for the different approaches. The different approaches are evaluated and a real-time implementation of the most promising approach is presented. The book includes topics related to speech coding, pattern- / speech recognition, speech enhancement, statistics and digital signal processing in general.

Over the last decade a number of research areas have contributed to the concept of advanced intelligent environments, these include ubiquitous computing, pervasive computing, embedded intelligence, intelligent user interfaces, human factors, intelligent buildings, mobile communications, domestic robots, intelligent sensors, artistic and architectural design and ambient intelligence. Undeniably, multimodal spoken language dialogue interaction is a key factor in ensuring natural interaction and therefore of particular interest for advanced intelligent environments. The book covers all the...

Speech and Human-Machine Dialog focuses on the dialog management component of a spoken language dialog system. Spoken language dialog systems provide a natural interface between humans and computers. These systems are of special interest for interactive applications, and they integrate several technologies including speech recognition, natural language understanding, dialog management and speech synthesis.

Due to the conjunction of several factors throughout the past few years, humans are significantly changing their behavior vis-a-vis machines. In particular, the...

In this work, the authors present a fully statistical approach to model non--native speakers' pronunciation. Second-language speakers pronounce words in multiple different ways compared to the native speakers. Those deviations, may it be phoneme substitutions, deletions or insertions, can be modelled automatically with the new method presented here.

The methods is based on a discrete hidden Markov model as a word pronunciation model, initialized on a standard pronunciation dictionary. The implementation and functionality of the methodology has been proven and verified with a test set...

In this work, the authors present a fully statistical approach to model non--native speakers' pronunciation. Second-language speakers pronounce words in multiple different ways compared to the native speakers. Those deviations, may it be phoneme substitutions, deletions or insertions, can be modelled automatically with the new method presented here.

The methods is based on a discrete hidden Markov model as a word pronunciation model, initialized on a standard pronunciation dictionary. The implementation and functionality of the methodology has been proven and verified with a test set...