Speech signal enhancement using neural network and wavelet transform
Speech enhancement is concerned with the processing of corrupted or noisy speech signal in order to improve the quality or intelligibility of the signal. Our goal is to enhance speech signal corrupted by noise to obtain a clean signal with higher quality. However, the presence of noise in speech sig...
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| creator | Daqrouq, K. Abu-Isbeih, I.N. Alfauri, M. |
| description | Speech enhancement is concerned with the processing of corrupted or noisy speech signal in order to improve the quality or intelligibility of the signal. Our goal is to enhance speech signal corrupted by noise to obtain a clean signal with higher quality. However, the presence of noise in speech signals will contribute to a high degree of inaccuracy in a system that requires speech processing. This idea of noise cancellation for the speech signal was processed through the neural networks. Three methods were tested: 1. The adaptive linear neuron (ADALINE). 2. feed forward neural network enhancement method FFNN 3. wavelet transform and Adaline enhancement Method. The results obtained showed high quality due to fast processing and high signal-noise-ratio. The tested signal was enhanced 10 dB by Adaline, 3 dB by FFNN and 8 dB by Wavelet Transform and Adaline Enhancement Method. |
| doi_str_mv | 10.1109/SSD.2009.4956823 |
| format | Conference Proceeding |
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Our goal is to enhance speech signal corrupted by noise to obtain a clean signal with higher quality. However, the presence of noise in speech signals will contribute to a high degree of inaccuracy in a system that requires speech processing. This idea of noise cancellation for the speech signal was processed through the neural networks. Three methods were tested: 1. The adaptive linear neuron (ADALINE). 2. feed forward neural network enhancement method FFNN 3. wavelet transform and Adaline enhancement Method. The results obtained showed high quality due to fast processing and high signal-noise-ratio. 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The tested signal was enhanced 10 dB by Adaline, 3 dB by FFNN and 8 dB by Wavelet Transform and Adaline Enhancement Method.</description><subject>Discrete wavelet transform</subject><subject>Feedforward neural networks</subject><subject>Feeds</subject><subject>Neural network</subject><subject>Neural networks</subject><subject>Neurons</subject><subject>Noise cancellation</subject><subject>Signal processing</subject><subject>Speech enhancement</subject><subject>Speech processing</subject><subject>Speech signal</subject><subject>Testing</subject><subject>Wavelet transforms</subject><isbn>1424443458</isbn><isbn>9781424443451</isbn><isbn>9781424443468</isbn><isbn>1424443466</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1UEtLw0AYXJGCtuYueNk_kLrv7B6l9QUFD-m9fO5-aaPJtuymFv-9EetchmGGYRhCbjmbc87cfV0v54IxN1dOGyvkBSlcZbkSSimpjL0k03-h7YRMf7OOCcXkFSly_mAjlBbWVtdkWR8Q_Y7mdhuhoxh3ED32GAd6zG3c0ojHNBoRh9M-fVKIgZ7gCzsc6JAg5maf-hsyaaDLWJx5RtZPj-vFS7l6e35dPKzK1rGhlNYxLgNUBk0jPWhwPlTqPTAZUDcQvNR6nCosa7xRZrSFkBIEclM5JeSM3P3Vtoi4OaS2h_S9OZ8gfwBSSU3d</recordid><startdate>200903</startdate><enddate>200903</enddate><creator>Daqrouq, K.</creator><creator>Abu-Isbeih, I.N.</creator><creator>Alfauri, M.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200903</creationdate><title>Speech signal enhancement using neural network and wavelet transform</title><author>Daqrouq, K. ; Abu-Isbeih, I.N. ; Alfauri, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-389013da76e6f3ca5a9cd74bd03de5fadc355009280fc646a9c2233a2e1679423</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Discrete wavelet transform</topic><topic>Feedforward neural networks</topic><topic>Feeds</topic><topic>Neural network</topic><topic>Neural networks</topic><topic>Neurons</topic><topic>Noise cancellation</topic><topic>Signal processing</topic><topic>Speech enhancement</topic><topic>Speech processing</topic><topic>Speech signal</topic><topic>Testing</topic><topic>Wavelet transforms</topic><toplevel>online_resources</toplevel><creatorcontrib>Daqrouq, K.</creatorcontrib><creatorcontrib>Abu-Isbeih, I.N.</creatorcontrib><creatorcontrib>Alfauri, M.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Daqrouq, K.</au><au>Abu-Isbeih, I.N.</au><au>Alfauri, M.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Speech signal enhancement using neural network and wavelet transform</atitle><btitle>2009 6th International Multi-Conference on Systems, Signals and Devices</btitle><stitle>SSD</stitle><date>2009-03</date><risdate>2009</risdate><spage>1</spage><epage>6</epage><pages>1-6</pages><isbn>1424443458</isbn><isbn>9781424443451</isbn><eisbn>9781424443468</eisbn><eisbn>1424443466</eisbn><abstract>Speech enhancement is concerned with the processing of corrupted or noisy speech signal in order to improve the quality or intelligibility of the signal. Our goal is to enhance speech signal corrupted by noise to obtain a clean signal with higher quality. However, the presence of noise in speech signals will contribute to a high degree of inaccuracy in a system that requires speech processing. This idea of noise cancellation for the speech signal was processed through the neural networks. Three methods were tested: 1. The adaptive linear neuron (ADALINE). 2. feed forward neural network enhancement method FFNN 3. wavelet transform and Adaline enhancement Method. The results obtained showed high quality due to fast processing and high signal-noise-ratio. The tested signal was enhanced 10 dB by Adaline, 3 dB by FFNN and 8 dB by Wavelet Transform and Adaline Enhancement Method.</abstract><pub>IEEE</pub><doi>10.1109/SSD.2009.4956823</doi><tpages>6</tpages></addata></record> |
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| ispartof | 2009 6th International Multi-Conference on Systems, Signals and Devices, 2009, p.1-6 |
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| language | eng |
| recordid | cdi_ieee_primary_4956823 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Discrete wavelet transform Feedforward neural networks Feeds Neural network Neural networks Neurons Noise cancellation Signal processing Speech enhancement Speech processing Speech signal Testing Wavelet transforms |
| title | Speech signal enhancement using neural network and wavelet transform |
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