本論文主要使用動態型顯樹量化進階音訊編碼器(Advanced Audio Coding, AAC)的修正型離散餘弦轉換係數(modified discrete cosine transform coefficients, MDCT coefficients)，並且在過程中進行位元分配。我們使用動態明顯樹量化法(Dynamic significance tree quantization, DSTQ)，此外也使用層級樹集合分派法(Set partitioning in hierarchical trees, SPIHT)，和結合明顯樹量化法(Combined significance tree quantization, CSTQ)，MPEG-1 layer 3 (MP3)和開放的音源編碼軟體Ogg Vorbis來對經過心理聲學處理和未經過心理聲學處理的修正型離散餘弦轉換係數做編碼。實驗資料庫包含有12種不同類別音訊，即男聲、女聲、吉他、琵琶、揚琴、嗩吶、鋼琴、交響樂、二胡、爵士樂、薩克斯風、以及笛子。實驗的位元率有32 kbps、48 kbps、64 kbps、及96 kbps。實驗結果發現在這些位元率下，所有使用明顯樹模型量化離散餘弦轉換係數之編碼後音訊依然可以保有相當接近原音的音訊品質。在各種樹模型中，又以加入心裡聲學的DSTQ模型(psy-DSTQ-512)在聲音感知量測的模擬中表現最佳。

In this thesis, we employ dynamic significance tree quantization (DSTQ) to quantize the modified discrete cosine transform coefficients (MDCT) of audio signals and at the same time to carry on the bit allocation during the encoding process. We compare DSTQ with other famous encoding methods including set partitioning in hierarchical trees (SPIHT), combined significance tree quantization (CSTQ), MPEG-1 layer 3 (MP3), and open source audio encoding software Ogg Vorbis. It is also investigated for each significance tree model method that the psychoacoustic model is either included or not included within the encoder. The experimental database contains 12 categories of audio signals, i.e., male voices, female voices, guitar, lute, dulcimer, suona, piano, symphony, erhu, jazz, saxophone, and flute. Encoded bit-rates are set to be 32 kbps, 48 kbps, 64 kbps, and 96 kbps, respectively. The experimental results show that all of the significance tree models can maintain nearly transparent audio quality at these bit rates mentioned above. Among them, DSTQ with psychoacoustic model (psy-DSTQ-512) performs the best in our simulation based on the perceptual evaluation of audio quality (PEAQ) measure.

摘要 i
ABSTRACT ii
誌謝 iii
目 錄 iv
表目錄 vi
圖目錄 vii
第一章 緒論 1
1.1研究動機與背景 1
1.2音訊編碼簡介 2
1.3論文架構 2
第二章 進階音訊編碼器......3
2.1進階音訊編碼器的由來....3
2.2進階音訊編碼器架構......4
2.2.1 濾波器...............8
2.2.1.1 視窗選擇...........8
2.2.2 增益控制.............9
2.2.3 心理聲學............11
2.2.3.1 臨界頻帶......... 12
2.2.3.2 遮蔽效應..........13
2.2.4 暫態雜訊修整........15
2.2.5立體聲編碼...........15
2.2.5.1 強度立體聲編碼....15
2.2.5.2 中側立體聲編碼....16
第三章 使用樹模型之低位元率量化....... 17
3.1 位元分配與量化..... ..........17
3.2 比例係數頻帶與比例係數...... 18
3.3 位元分配與量化 ..........19
3.4 SPIHT演算法 ..........20
3.5 CSTQ演算法 ..........23
3.6 DSTQ演算法 ..........25
3.6.1 DSTQ-512、DSTQ-128、DSTQ-32.....29
第四章 實驗結果與討論 30
4.1 實驗環境及音訊 30
4.2 客觀分數量測方法 31
4.2.1 聲音感知量測 .........31
4.2.2 分段訊雜比 ..........43
第五章 結論及未來展望........50
5.1 結論 ....................50
5.2 未來展望.................50
參考文獻 ...................51

[1] M. Bosi,et al., “ISO/IEC MPEG-2 advanced audio coding,” Journal of Audio Engineering Society, vol.45, October 1997, pp. 789-814.
[2] ISO/IEC 19818-7,“ Information technology, generic coding of moving picturter and associated audio information, Part7: Advance Audio Coding,” 2002.
[3] M. Wolters, K. Kjorling, D.Homm, and H. Purnhagen, “A closer look into MPEG-4 high efficiency AAC,” 115th AES Conventio, New York, October 2003.
[4] Z. Lu and W. A. Pearlman, “An efficient, low complexity audio coder delivering multiple levels of quality for interactive applications,” Multimedia Signal Processing, Redondo Beach, Dec. 1998, pp. 529–534.
[5] J. M. Shaprio, “Embedded image coding using zerotrees of wavelet coefficients,” IEEE Trans. on Signal Processing, vol. 41, no. 12, Dec. 1993, pp. 3445-3463.
[6] K. Brandenburg, “MP3 and AAC explained,” presented at the 17” AkS Conference on Hith Quality Audio Coding, Florence, 1999.
[7] M. Raad and A. Mertins, “From lossy to lossless audio coding using set partitioning in hierarchical trees,” Digital Audio Effects, Hamburg, Germany, Sep. 2002, pp. 245–250.
[8] Te Li, S. Rahardja, Soo Ngee Koh, ”Frequency region-based prioritized bit-plane coding for scalable audio,” IEEE Trans. on Audio, Speech and Language Processing, vol. 16, no. 12, Jan 2008, pp. 94-105.
[9] ITU-R Recommendation BS.1387-1, Perceptual evaluation of audio quality (PEAQ): An method for objective of perceived audio quality, 1998-2001.
[10] ITU-R Recommendation BS.1387, Perceptual evaluation of audio quality (PEAQ): A method for objective of perceived audio quality, 1998.
[11] M. S. Lewicki, “Efficient coding of natural sounds,” Nature Neuroscience, vol. 5, no. 4, Mar. 2002, pp.356-363.
[12] C. D. Creusere, “Understanding perceptual distortion in MPEG scalable audio coding,” IEEE Trans. on Signal Processing, vol. 13, no. 3, May. 2005, pp. 422-431.
[13] 陳景銘，利用高頻重建之MPEG音訊編解碼器設計及其系統實現，碩士論文，國立雲林科技大電子與資訊工程研究所，雲林，2004。
[14] 王小川，語音訊號處理，台北，全華，民國93年。
[15] Z. Lu, W. A. Peerman, “High quality scalable stereo audio coding,” 1999. [Online].Available:http://www.cipr.rpi.edu/pearlman/papers/scal audio.ps.gz .
[16] S. Strahl, H. Hansen, and A. Mertins, “A dynamic fine-grain scalable compression scheme,“ IEEE Trans. on Audio, Speech and Language Processing, vol. 19, no. 1, Jan. 2001, pp. 14-23.
[17] O. Kunz, “SBR explained: White paper,” Coding Technologies.
[18] A. Said and W. A. Pearman, ”A new fast and efficient image codec based on set partitioning in hierarchical trees,” IEEE Trans. on Circuit and Systems for Video Technology, vol. 6, no.3, June. 1996, pp. 243-250.
[19] T. Painter and A. Spanias, “Perceptual coding of digital audio,” Proc. IEEE, vol. 88, Apr. 2000, pp. 451-513.