Pseudo-Syntactic Language Modeling for Disfluent Speech Recognition
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The goal of the AMIDA mini-project is to transfer some of the technologies developed within the AMIDA project to be used by a Klewel retrieval system. More specifically, the main focus is to develop a speech-to-text application based on the AMIDA Automatic ...
Research on automatic recognition of named entities from Arabic text uses techniques that work well for the Latin based languages such as local grammars, statistical learning models, pattern matching, and rule-based techniques. These techniques boost their ...
This paper presents a bi-modal (face and speech) authentication demonstration system that simulates the login of a user using its face and its voice. This demonstration is called BioLogin. It runs both on Linux and Windows and the Windows version is freely ...
In this work, we propose different strategies for efficiently integrating an automated speech recognition module in the framework of a dialogue-based vocal system. The aim is the study of different ways leading to the improvement of the quality and robustn ...
The recognition of speech in meetings poses a number of challenges to current Automatic Speech Recognition (ASR) techniques. Meetings typically take place in rooms with non-ideal acoustic conditions and significant background noise, and may contain large s ...
This paper presents a bi-modal (face and speech) authentication demonstration system that simulates the login of a user using its face and its voice. This demonstration is called BioLogin. It runs both on Linux and Windows and the Windows version is freely ...
This article compares one-dimensional and multi-dimensional dialogue act tagsets used for automatic labeling of utterances. The influence of tagset dimensionality on tagging accuracy is first discussed theoretically, then based on empirical data from human ...
This paper investigates the use of unlabeled data to help labeled data for audio-visual event recognition in meetings. To deal with situations in which it is difficult to collect enough labeled data to capture event characteristics, but collecting a large ...
This paper investigates the use of unlabeled data to help labeled data for audio-visual event recognition in meetings. To deal with situations in which it is difficult to collect enough labeled data to capture event characteristics, but collecting a large ...
Juicer is a decoder for HMM-based large vocabulary speech recognition that uses a weighted finite state transducer (WFST) representation of the search space. The package consists of a number of command line utilities: the Juicer decoder itself, along with ...