Noise Estimation and Noise Removal Techniques for Speech Recognition in Adverse Environment

Abstract : Noise is ubiquitous in almost all acoustic environments. The speech signal, that is recorded by a microphone is generally infected by noise originating from various sources. Such contamination can change the characteristics of the speech signals and degrade the speech quality and intelligibility, thereby causing significant harm to human-to-machine communication systems. Noise detection and reduction for speech applications is often formulated as a digital filtering problem, where the clean speech estimation is obtained by passing the noisy speech through a linear filter. With such a formulation, the core issue of noise reduction becomes how to design an optimal filter that can significantly suppress noise without noticeable speech distortion. This paper focuses on voice activity detection, noise estimation, removal techniques and an optimal filter.
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Communication dans un congrès
Zhongzhi Shi; Sunil Vadera; Agnar Aamodt; David Leake. 6th IFIP TC 12 International Conference on Intelligent Information Processing (IIP), Oct 2010, Manchester, United Kingdom. Springer, IFIP Advances in Information and Communication Technology, AICT-340, pp.336-342, 2010, Intelligent Information Processing V. 〈10.1007/978-3-642-16327-2_40〉
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Dernière modification le : vendredi 11 août 2017 - 14:51:00
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Urmila Shrawankar, Vilas Thakare. Noise Estimation and Noise Removal Techniques for Speech Recognition in Adverse Environment. Zhongzhi Shi; Sunil Vadera; Agnar Aamodt; David Leake. 6th IFIP TC 12 International Conference on Intelligent Information Processing (IIP), Oct 2010, Manchester, United Kingdom. Springer, IFIP Advances in Information and Communication Technology, AICT-340, pp.336-342, 2010, Intelligent Information Processing V. 〈10.1007/978-3-642-16327-2_40〉. 〈hal-01055058〉

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