Duration modeling is a fundamental task of prosody generation for Text To Speech (TTS) systems. The objective of this task is to predict the duration of a speech unit from its phonological representation. Duration modeling has a significant influence on the intelligibility and the naturalness of the synthesized speech. This paper presents a Neural Network (NN) based approach to predict the dura...

Given a speech recognition hypothesis, a dialogue system has the choice of accepting or rejecting this hypothesis, but can also choose to provide evidence of understanding, such as a clarification request, or display its understanding. In 3.3.2.7, this choice was referred to as the grounding decision problem. In the previous chapters, a static model with hand-crafted thresholds was used. In thi...

In robotics, learning from demonstration is a research field that has gained a lot of attention since it provides an easy and intuitive way to teach a robot complex movements. When teaching a human it is common to use natural language to provide additional information. Regardless of that, it is rarely investigated how speech can be used in addition for teaching a robot with learning from demons...

Modern developments in machine learning methodology have produced effective approaches to speech emotion recognition. The field of data mining is widely employed numerous situations where it possible predict future outcomes by using the input sequence from previous training data. Since feature space and distribution are same for both testing conventional approaches, they drawn pool. However, be...

This paper focuses on the user experience (UX) of a simultaneous interpretation system for face-to-face conversation between two users. To assess the UX of the system, we first made a transcript of the speech of users recorded during a task-based evaluation experiment and then analyzed user speech from the viewpoint of UX. In a task-based evaluation experiment, 44 tasks out of 45 tasks were sol...

We propose a new model adaptation method based on the histogram equalization technique for providing robustness in noisy environments. The trained acoustic mean models of a speech recognizer are adapted into environmentally matched conditions by using the histogram equalization algorithm on a single utterance basis. For more robust speech recognition in the heavily noisy conditions, trained aco...

Shortening speech prompts reduce attention allocation display; but might on the other hand deteriorate the users’ mental model. Thus the paper investigates effects of reducing time effort of speech via a transfer task, retrieval tasks and navigation-orientation tasks for three different strategies: (1) using earcons for menu orientation, (2) using commando based speech for interaction options, ...

the present study was conducted to compare the effect of individual and group pre-task planning on efl learners’ accuracy and complexity in speaking. to fulfill the purpose of the study, 60 intermediate female learners at the first grade of high school were chosen by means of a sample preliminary english test (pet) and randomly divided into two experimental groups of 30 students; the individual...