| Item type |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2008-12-16 |
| タイトル |
|
|
タイトル |
Fast Implementation of KLT-Based Speech Enhancement Using Vector Quantization |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
Complexity |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
Karhunen-Loeve transform(KLT) |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
speech enhancement |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
subspace |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
vector quantization |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| 著者 |
Nagata, Yoshifumi
Mitsubori, Kenji
Kagi, Takahiko
Fujioka, Toyota
Abe, Masato
|
| 著者(機関) |
|
|
値 |
Department of Computer and Information Sciences, Iwate University |
| 登録日 |
|
|
日付 |
2008-12-16 |
| 書誌情報 |
IEEE Transactions on Audio Speech and Language Processing
巻 14,
号 6,
p. 2086-2097,
発行日 2006-01-01
|
| ISSN |
|
|
収録物識別子タイプ |
ISSN |
|
収録物識別子 |
1558-7916 |
| Abstract |
|
|
内容記述タイプ |
Other |
|
内容記述 |
We propose a new method for implementing Karhunen–Loeve transform (KLT)-based speech enhancement to exploit vector quantization (VQ). The method is suitable for real-time processing. The proposed method consists of a VQ learning stage and a filtering stage. In the VQ learning stage, the autocorrelation vectors comprising the first$K$elements of the autocorrelation function are extracted from learning data. The autocorrelation vectors are used as codewords in the VQ codebook. Next, the KLT bases that correspond to all the codeword vectors are estimated through eigendecomposition (ED) of the empirical Toeplitz covariance matrices constructed from the codeword vectors. In the filtering stage, the autocorrelation vectors that are estimated from the input signal are compared to the codewords. The nearest one is chosen in each frame. The precomputed KLT bases corresponding to the chosen codeword are used for filtering instead of performing ED, which is computationally intensive. Speech quality evaluation using objective measures shows that the proposed method is comparable to a conventional KLT-based method that performs ED in the filtering process. Results of subjective tests also support this result. In addition, processing time is reduced to about 1/66 that of the conventional method in the case where a frame length of 120 points is used. This complexity reduction is attained after the computational cost in the learning stage and a corresponding increase in the associated memory requirement. Nevertheless, these results demonstrate that the proposed method reduces computational complexity while maintaining the speech quality of the KLT-based speech enhancement. |
| 出版者 |
|
|
出版者 |
IEEE |
| 権利 |
|
|
権利情報 |
© 2006 IEEE |
| DOI |
|
|
関連タイプ |
isIdenticalTo |
|
|
識別子タイプ |
DOI |
|
|
関連識別子 |
10.1109/TASL.2006.872622 |
| 著者版フラグ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
itaslp-v14n6p2086-2097.pdf (935.6 kB)
