Get rid of the noise! : A speech enhancement technology using microphone arrays
This report is to experiment and compare the different performances of two different deep learning networks on denoising speech signals using MATLAB. Through this experiment, Short-time Fourier Transform is used to process the speech audio signals to analyze the clean and noise signals, then generat...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/149292 |
| _version_ | 1826127361848901632 |
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| author | Cai, Zihui |
| author2 | Andy Khong W H |
| author_facet | Andy Khong W H Cai, Zihui |
| author_sort | Cai, Zihui |
| collection | NTU |
| description | This report is to experiment and compare the different performances of two different deep learning networks on denoising speech signals using MATLAB. Through this experiment, Short-time Fourier Transform is used to process the speech audio signals to analyze the clean and noise signals, then generate the targets to make predictions for noise signals, and finally remove the noise from speech signals. The two networks used are Fully Connected Network (FCN) and Convolutional Neural Network (CNN). The parameters compared are the training time duration, the total number of weights, the quality of the denoised signal compared to the clean signal. |
| first_indexed | 2024-10-01T07:07:38Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/149292 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:07:38Z |
| publishDate | 2021 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1492922023-07-07T18:09:50Z Get rid of the noise! : A speech enhancement technology using microphone arrays Cai, Zihui Andy Khong W H School of Electrical and Electronic Engineering zcai004@e.ntu.edu.sg, AndyKhong@ntu.edu.sg Engineering::Electrical and electronic engineering This report is to experiment and compare the different performances of two different deep learning networks on denoising speech signals using MATLAB. Through this experiment, Short-time Fourier Transform is used to process the speech audio signals to analyze the clean and noise signals, then generate the targets to make predictions for noise signals, and finally remove the noise from speech signals. The two networks used are Fully Connected Network (FCN) and Convolutional Neural Network (CNN). The parameters compared are the training time duration, the total number of weights, the quality of the denoised signal compared to the clean signal. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-05-29T10:49:27Z 2021-05-29T10:49:27Z 2021 Final Year Project (FYP) Cai, Z. (2021). Get rid of the noise! : A speech enhancement technology using microphone arrays. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149292 https://hdl.handle.net/10356/149292 en A3019-201 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Cai, Zihui Get rid of the noise! : A speech enhancement technology using microphone arrays |
| title | Get rid of the noise! : A speech enhancement technology using microphone arrays |
| title_full | Get rid of the noise! : A speech enhancement technology using microphone arrays |
| title_fullStr | Get rid of the noise! : A speech enhancement technology using microphone arrays |
| title_full_unstemmed | Get rid of the noise! : A speech enhancement technology using microphone arrays |
| title_short | Get rid of the noise! : A speech enhancement technology using microphone arrays |
| title_sort | get rid of the noise a speech enhancement technology using microphone arrays |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/149292 |
| work_keys_str_mv | AT caizihui getridofthenoiseaspeechenhancementtechnologyusingmicrophonearrays |