Non-intrusive objective evaluation of speech quality in noisy condition
| Autor: | A. N. M. Shahriyar Hossain, Md. Numan Hasan, Md. Ashequr Rahman, Md. Rafidul Islam, Mohammad Ariful Haque, Ahmed Nazim Uddin |
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| Rok vydání: | 2016 |
| Předmět: |
Computer science
business.industry Speech recognition Feature extraction Speech coding 020206 networking & telecommunications Pattern recognition 02 engineering and technology Speech processing Linear predictive coding Support vector machine 030507 speech-language pathology & audiology 03 medical and health sciences Statistical classification 0202 electrical engineering electronic engineering information engineering Artificial intelligence 0305 other medical science business PESQ Test data |
| Zdroj: | 2016 9th International Conference on Electrical and Computer Engineering (ICECE). |
| Popis: | It is very difficult, if not impossible, to obtain a clean reference signal of a noisy speech recorded in a practical environment. As a result, intrusive methods that evaluate the quality of speech signal with the help of a clean reference signal has little value in real world applications. In this paper, we investigate the effectiveness of data-driven non-intrusive method for assessing quality of speech without using clean reference signal. In the proposed method, a support vector machine based classifier is trained using a labelled dataset and then the classifier provides speech assessment rating on unknown speech signals. The obtained results have been evaluated against the intrusive PESQ score. The results indicate that the proposed technique performs better than the state-of-the-art non-intrusive methods on the same test data set. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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