In this paper, we explore the use of Random Forests (RFs) in the structured language model (SLM), which uses rich syntactic information in predicting the next word based on words ...
In this paper we demonstrate that Long Short-Term Memory (LSTM) is a differentiable recurrent neural net (RNN) capable of robustly categorizing timewarped speech data. We measure ...
In spontaneous speech, speakers segment their speech into intonational phrases, and make repairs to what they are saying. However, techniques for understanding spontaneous speech ...
Hidden Markov models play a critical role in the modelling and problem solving of important AI tasks such as speech recognition and natural language processing. However, the stude...
This paper presents a novel approach to speech recognition using fuzzy modeling. The task begins with conversion of speech spectrogram into a linguistic description based on arbit...
This paper describes the design and development of a set of signal processing software tools for speech recognition. The tools were developed for inclusion in a comprehensive publ...
Hualin Gao, Richard Duncan, Julie Baca, Joseph Pic...
: Developing a speech-based application for mobile devices requires work upfront, since mobile devices and speech recognition systems vary dramatically in their capabilities. While...
Werner Kurschl, Stefan Mitsch, Rene Prokop, Johann...
Some big languages like English are spoken by a lot of people whose mother tongues are different from. Their second languages often have not only distinct accent but also differen...
In this paper we discuss the design, acquisition and preprocessing of a Czech audio-visual speech corpus. The corpus is intended for training and testing of existing audio-visual ...
Large speech and text corpora are crucial to the development of a state-of-the-art speech recognition system. This paper reports on the construction and evaluation of the first Th...