Vector quantization and its application to speech coding
This thesis is devoted to the investigation of vector quantization for speech coding. The soundness of the code-excited linear prediction (CELP) and multi-band excitation (MBE) speech production models has been verified by the fact that the speech coders based on these models are able to synthesize...
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| Format: | Thesis |
| Language: | English |
| Published: |
2008
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| Online Access: | http://hdl.handle.net/10356/13141 |
| _version_ | 1826111630224654336 |
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| author | Chen, Changqian. |
| author2 | Koh, Soo Ngee |
| author_facet | Koh, Soo Ngee Chen, Changqian. |
| author_sort | Chen, Changqian. |
| collection | NTU |
| description | This thesis is devoted to the investigation of vector quantization for speech coding. The soundness of the code-excited linear prediction (CELP) and multi-band excitation (MBE) speech production models has been verified by the fact that the speech coders based on these models are able to synthesize high quality speech signals. However, such coders do not perform satisfactorily at bit rates lower than certain known thresholds. This opens up the possibility for the bit rates necessary for satisfactory speech representation to be reduced further, by describing more concisely the LPC parameters of the CELP model and the spectral magnitudes in the MBE model. That is, efficient representation of model parameters is a means to achieving or improving low bit rate speech coding, although efforts to enhance the model itself may also lead to some improvements. |
| first_indexed | 2024-10-01T02:53:54Z |
| format | Thesis |
| id | ntu-10356/13141 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:53:54Z |
| publishDate | 2008 |
| record_format | dspace |
| spelling | ntu-10356/131412023-07-04T15:07:11Z Vector quantization and its application to speech coding Chen, Changqian. Koh, Soo Ngee School of Electrical and Electronic Engineering Sivaprakasapillai, Pratab DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence DRNTU::Engineering::Computer science and engineering::Data::Coding and information theory This thesis is devoted to the investigation of vector quantization for speech coding. The soundness of the code-excited linear prediction (CELP) and multi-band excitation (MBE) speech production models has been verified by the fact that the speech coders based on these models are able to synthesize high quality speech signals. However, such coders do not perform satisfactorily at bit rates lower than certain known thresholds. This opens up the possibility for the bit rates necessary for satisfactory speech representation to be reduced further, by describing more concisely the LPC parameters of the CELP model and the spectral magnitudes in the MBE model. That is, efficient representation of model parameters is a means to achieving or improving low bit rate speech coding, although efforts to enhance the model itself may also lead to some improvements. Doctor of Philosophy (EEE) 2008-08-29T02:46:56Z 2008-10-20T07:15:51Z 2008-08-29T02:46:56Z 2008-10-20T07:15:51Z 1998 1998 Thesis http://hdl.handle.net/10356/13141 en 196 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence DRNTU::Engineering::Computer science and engineering::Data::Coding and information theory Chen, Changqian. Vector quantization and its application to speech coding |
| title | Vector quantization and its application to speech coding |
| title_full | Vector quantization and its application to speech coding |
| title_fullStr | Vector quantization and its application to speech coding |
| title_full_unstemmed | Vector quantization and its application to speech coding |
| title_short | Vector quantization and its application to speech coding |
| title_sort | vector quantization and its application to speech coding |
| topic | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence DRNTU::Engineering::Computer science and engineering::Data::Coding and information theory |
| url | http://hdl.handle.net/10356/13141 |
| work_keys_str_mv | AT chenchangqian vectorquantizationanditsapplicationtospeechcoding |