M. Mehdi Homayounpour

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Discrimination ability of speech long term features, including jitters, shimmers and mean MFCC is proposed, for age interval and sex identification. First to make a primary study of discrimination ability, two well-known unsupervised classification methods, i.e. k-means and FCM, were used. Then, two supervised discriminative classification approaches,(More)
This paper presents a new feature set for noisy speech recognition in autocorrelation domain. The autocorrelation domain is well-known for its pole preserving and noise separation properties. Therefore, in this paper we use the autocorrelation domain as an appropriate candidate for robust feature extraction. In our approach, initially, the lower lags of the(More)
Construction of letter to sound (LTS) conversion systems in Farsi language is a difficult task, and because of the omission of some vowels in Farsi orthography, these systems in general have low efficiencies. In this paper, the structure of a letter to sound system, having a three-layers architecture, has been presented. The first layer is rule-based, and(More)
Voice over internet protocol, and in particular speech quality assessment and prediction, is an active area of research. Many methods have been developed for the quality assessment of the transmitted speech, including intrusive and non-intrusive methods. In general, non-intrusive methods are appropriate for live speech quality assessment. Recently proposed(More)
Text normalization is one of the most important tasks in text processing and text to speech conversion. In this paper, we propose a machine learning method to determine the type of Farsi language non-standard words (NSWs) by only using the structure of these words. Two methods including support vector machines (SVM) and classification and regression trees(More)
High accuracy phonetic segmentation is critical to achieve good quality in concatenative speech synthesis. However, the processing and inspection of a large amount of recorded speech will become a labor-intensive and error-prone job. In this paper, a post-refining method based on support vector machines (SVMs), is proposed for auto-segmentation of speech(More)