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Speech Analysis Based on AR Model Driven by t-Distribution Process
https://nitech.repo.nii.ac.jp/records/4173
https://nitech.repo.nii.ac.jp/records/4173d5e9f8cd-0e39-4101-b8b2-0c614bd48fb3
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
本文_fulltext (769.7 kB)
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Copyright (c) 1992 IEICE http://search.ieice.org/index.html
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| Item type | 学術雑誌論文 / Journal Article(1) | |||||||||||||||
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| 公開日 | 2012-11-07 | |||||||||||||||
| タイトル | ||||||||||||||||
| タイトル | Speech Analysis Based on AR Model Driven by t-Distribution Process | |||||||||||||||
| 言語 | en | |||||||||||||||
| 言語 | ||||||||||||||||
| 言語 | eng | |||||||||||||||
| 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 |
Sanubari, Junibakti
× Sanubari, Junibakti
× Wu, Yi-Jian
× Onoda, Mahoki
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| 著者別名 | ||||||||||||||||
| 姓名 | Tokuda, Keiichi | |||||||||||||||
| 言語 | en | |||||||||||||||
| 姓名 | 徳田, 恵一 | |||||||||||||||
| 言語 | ja | |||||||||||||||
| 姓名 | トクダ, ケイイチ | |||||||||||||||
| 言語 | ja-Kana | |||||||||||||||
| bibliographic_information |
en : IEICE transactions on fundamentals of electronics, communications and computer sciences 巻 E75-A, 号 9, p. 1159-1169, 発行日 1992-09-20 |
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| 出版者 | ||||||||||||||||
| 出版者 | Institute of Electronics, Information and Communication Engineers | |||||||||||||||
| 言語 | en | |||||||||||||||
| ISSN | ||||||||||||||||
| 収録物識別子タイプ | ISSN | |||||||||||||||
| 収録物識別子 | 0916-8508 | |||||||||||||||
| item_10001_source_id_32 | ||||||||||||||||
| 収録物識別子タイプ | NCID | |||||||||||||||
| 収録物識別子 | AA10826239 | |||||||||||||||
| 出版タイプ | ||||||||||||||||
| 出版タイプ | VoR | |||||||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||||||
| 内容記述 | ||||||||||||||||
| 内容記述タイプ | Other | |||||||||||||||
| 内容記述 | In this paper, a new M-estimation technique for the linear prediction analysis of speech is proposed. Since in the conventional linear prediction (CLP) method the obtained estimates are very much affected by the large amplitude residual parts, in the proposed method we use a loss function which assigns large weighting factor for small amplitude residuals and small weighting factor for large amplitude residuals which is for instance caused by the pitch excitations. The loss function is based on the assumption that the residual signal has an independent and identical t-distribution t(α) with α degrees of freedom. The efficiency of this new estimator depends on α. When α=, we get the CLP method. When the proposed method with small α is applied to the problems of estimating the formant frequencies and bandwidths of the synthetic speech by finding the roots of the prediction polynomial, we can achieve a more accurate and a smaller standard deviation (SD) estimate than that with large α. When the signal is very spiky, the proposed method can ahieve more efficient and accurate estimates than that with robust linear prediction (RBLP) method. The loss function is modified in the similar manner as the autocorrelation method. The solution is calculated by the Newton-Raphson iteration technique. The simulation results show that only few iterations are needed to reach a stationary point, the stationary point is always a local minimum and the obtained prediction filter is always minimum phase. Preliminary experiments on the human speech data indicate that the obtained results are insensitive to the placement of the analysis window and a higher spectral resolution than the CLP and RBLP method can be achieved. | |||||||||||||||
| 言語 | en | |||||||||||||||
