Real-time clarification filter of a dysphonic speech and its evaluation by listening experiments
نویسندگان
چکیده
This paper presents a digital filtering algorithm which clarifies dysphonic speech with the speaker’s individuality preserved. The study deals with the clarification of oesophageal speech and the speech of patients with cerebral palsy, and the filtering ability is being evaluated by listening experiments. Over 20,000 patients are currently suffered from laryngeal cancer in Japan, and the only treatment for the terminal symptoms requires the removal of the larynx including vocal cords. The authors are developing a clarification filtering algorithm of oesophageal speech, and the primal algorithm of software clarification and its effectiveness was reported in the previous ICDVRAT. Several algorithms for the clarification have been newly developed and implemented, and are being evaluated by questionnaires. The algorithms were extended and applied for the clarification of the speech by the patients of cerebral palsy.
منابع مشابه
A Real Time Adaptive Multiresolution Adaptive Wiener Filter Based On Adaptive Neuro-Fuzzy Inference System And Fuzzy evaluation
In this paper, a real-time denoising filter based on modelling of stable hybrid models is presented. Thehybrid models are composed of the shearlet filter and the adaptive Wiener filter in different forms.The optimization of various models is accomplished by the genetic algorithm. Next, regarding thesignificant relationship between Optimal models and input images, changing the structure of Optim...
متن کاملExamining the Association between T-unit and Pausing Length on the EFL Perception of Listening Comprehension
Listening taking over half of the learners’ time and effort (Nunan, 1998), forms a basis for acquiring much of a language. There are factors affecting listening comprehension and its perception, such as the speech rate, phonological properties of the text, the quality of the recording, the learners’ anxiety, and listening comprehension strategies (Goh, 2000; Hamouda, 2013). At the Iran Language...
متن کاملSpeech Enhancement by Modified Convex Combination of Fractional Adaptive Filtering
This paper presents new adaptive filtering techniques used in speech enhancement system. Adaptive filtering schemes are subjected to different trade-offs regarding their steady-state misadjustment, speed of convergence, and tracking performance. Fractional Least-Mean-Square (FLMS) is a new adaptive algorithm which has better performance than the conventional LMS algorithm. Normalization of LMS ...
متن کاملA Novel Frequency Domain Linearly Constrained Minimum Variance Filter for Speech Enhancement
A reliable speech enhancement method is important for speech applications as a pre-processing step to improve their overall performance. In this paper, we propose a novel frequency domain method for single channel speech enhancement. Conventional frequency domain methods usually neglect the correlation between neighboring time-frequency components of the signals. In the proposed method, we take...
متن کاملImproving the performance of MFCC for Persian robust speech recognition
The Mel Frequency cepstral coefficients are the most widely used feature in speech recognition but they are very sensitive to noise. In this paper to achieve a satisfactorily performance in Automatic Speech Recognition (ASR) applications we introduce a noise robust new set of MFCC vector estimated through following steps. First, spectral mean normalization is a pre-processing which applies to t...
متن کامل