Phoneme classification performance is a critical factor for the successful implementation of speech recognition system. A mispronunciation Arabic short vowels or long can change meaning complete sentence. However, correctly distinguishing phonemes with in Quranic recitation (the Holy book Muslims) still challenging problem even state-of-the-art methods, where duration considered one important f...

Lip-reading is a process of interpreting speech by visually analysing lip movements. Recent research in this area has shifted from simple word recognition to lip-reading sentences the wild. This paper attempts use phonemes as classification schema for explore an alternative and enhance system performance. Different schemas have been investigated, including character-based visemes-based schemas....

The study of traditional phonetics indicates the shape of lips takes important effect on the articulations of consonants and vowels. [1]. AVSP (Audio-Visual Speech Processing) can improve the naturalness of synthetical speech and recognition rate of the speech recognition system. Especially in computer-synthesized face, the movements of lip-shape play a crucial role. The present research aims t...

One potential area for improvement in continuous speech recognition is the modelling of phoneme transitions (not transition probabilties) arising from the non-stationarity of speech: refined models can then be used to compute probability distributions which can serve as emission probabilities for HMM-based speech recognition systems. In this paper we present our approach to improving phoneme tr...

Speech contains information of at least three sources the message that is being communicated, the speaker who is communicating and the environment. In this work we propose several approaches to improve the recognition of speech sounds that convey information about the message. We use phonemes which occur at the rate of few tens of milliseconds in the speech signal as basic units. Improvements i...

In this paper a new framework for acoustic model building is presented. It is based on non-uniform segment models, which are learned and scored with a time bidirectional recurrent neural network. While usually neural networks in speech recognition systems are used to estimate posterior "frame to phoneme" probabilities, they are used here to estimate directly "segment to phoneme" probabilities, ...

In this paper a new framework for acoustic model building is presented. It is based on non-uniform segment models, which are learned and scored with a time bidirectional recurrent neural network. While usually neural networks in speech recognition systems are used to estimate posterior "frame to phoneme" probabilities, they are used here to estimate directly "segment to phoneme" probabilities, ...

This paper proposes a new information retrieval method based on speech recognition results. Nowadays, there is huge speech data like news speech in TV and Radio broadcasts, etc. However, it is not easy to retrieve necessary information from these data because extra informations for retrieval are not attached to most of these data. To solve the problems, in this paper a Fuzzy retrieval method ba...