In spite of decades of research, Automatic Speech Recognition (ASR) is far from reaching the goal of performance close to Human Speech Recognition (HSR). One of the reasons for unsatisfactory performance of the state-of-the-art ASR systems, that are based largely on Hidden Markov Models (HMMs), is the inferior acoustic modeling of low level or phonetic level linguistic information in the speech...

Pure acoustic neural models, particularly the LSTM-RNN model, have shown great potential in language identification (LID). However, the phonetic information has been largely overlooked by most of existing neural LID models, although this information has been used in the conventional phonetic LID systems with a great success. We present a phone-aware neural LID architecture, which is a deep LSTM...

In this work we present our expert system of speech synthesis based on a text written in Standard Arabic, our work is carried out in two great stages: the creation of the sound data base, and the transformation of the written text into speech (Text To Speech TTS). This transformation is done firstly by a Phonetic Orthographical Transcription (POT) of any written Standard Arabic text that to tra...

This paper presents a novel approach to the identification of phonetic similarity using properties observed during the speech recognition process. An experiment is presented whereby specific phones are removed during the training phase of a statistical speech recognition system so that the behaviour of the system can be analysed to see which alternative phone is selected. The domain of the anal...

This paper presents a novel approach to the identification of phonetic similarity using properties observed during the speech recognition process. Experiments are presented whereby specific phones are removed during the training phase of a statistical speech recognition system so that the behaviour of the system can be analysed to see which alternative phone is selected. The domain of the analy...

In the last few years we have been experimenting with an automatic phonetic segmentation and labeling system based on a modified HMM phonetic recognizer followed by a local phonetic boundary refinement system. During this period we have used different approaches for the local refinement, including fuzzy rules and neural networks. In this paper we present a unified framework for the local refine...

CHENG-HONG YANG, CHENG-HUEI YANG, LI-YEH CHUANG AND CHING-HSING LUO Department of Electronic Engineering National Kaohsiung University of Applied Sciences Kaohsiung, 807 Taiwan Department of Telecommunication and Computer Engineering National Kaohsiung Institute of Marine Technology Kaohsiung, 811 Taiwan Department of Chemical Engineering I-Shou University Kaohsiung, 840 Taiwan Department of El...