The interest in text to speech synthesis increased in the world . text to speech have been developed for many popular languages such as English, Spanish and French and many researches and developments have been applied to those languages. Persian on the other hand, has been given little attention compared to other languages of similar importance and the research in Persian is still in its infan...

Previous studies have shown that segmentation skills are language-specific, making it difficult to segment continuous speech in an unfamiliar language into its component words. Here we present the first study capturing the delay in segmentation and recognition in the foreign listener using ERPs. We compared the ability of Dutch adults and of English adults without knowledge of Dutch ('foreign l...

This paper proposes a new technique for speech feature estimation under noise circumstances. This new approach yields noise-robust continuous speech recognition (CSR). Noiserobust techniques for isolated word speech recognition typically employ the running spectrum analysis (RSA), the running spectrum filtering (RSF) and the dynamic range adjustment (DRA) methods. Among them, only RSA has been ...

In this paper, a CNN-based structure for the time-frequency localization of information is proposed Persian speech recognition. Research has shown that receptive fields’ spectrotemporal plasticity some neurons in mammals’ primary auditory cortex and midbrain makes facilities improve recognition performance. Over past few years, much work been done to localize ASR systems, using spatial or tempo...

This paper presents a new two-pass algorithm for Extra Large (more than 1M words) Vocabulary COntinuous Speech recognition based on the Information Retrieval (ELVIRCOS). The principle of this approach is to decompose a recognition process into two passes where the first pass builds the words subset for the second pass recognition by using information retrieval procedure. Word graph composition ...

This paper presents a two-pass algorithm for Extra Large (more than 1M words) Vocabulary COntinuous Speech recognition based on the Information Retrieval (ELVIRCOS). The principle of this approach is to decompose a recognition process into two passes where the first pass builds the word subset for the second pass recognition by using information retrieval procedure. Word graph composition for c...

We present a new search algorithm for very large vocabulary continuous speech recognition. Continuous speech recognition with this algorithm is only about 10 times more computationally expensive than isolated word recognition. We report preliminary recognition results obtained by testing our recognizer on "books on tape" using a 60,000 word dictionary.

Spelling recognition is an approach to enhance a speech recognizer to cope with incorrectly recognized words and out-of-vocabulary words. This paper presents a general framework for Thai speech recognition, enhanced with spelling recognition. To implement Thai spelling recognition, Thai alphabets and their spelling methods are analyzed. Based on hidden Markov models, we propose a method to cons...

the geometric distribution of states duration is one of the main performance limiting assumptions of hidden markov modeling of speech signals. stochastic segment models, generally, and segmental hmm, specifically, overcome this deficiency partly at the cost of more complexity in both training and recognition phases. in this paper, a new duration modeling approach is presented. the main idea of ...