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[4] Roch M A, Scott Brandes T, Patel B, et al. Automated [12] 刘悦, 王晓婷. 短时频域分形端点检测算法 [J]. 微电子学与计
extraction of odontocete whistle contours[J]. The Jour- 算机, 2015, 32(9): 81–84, 89.
nal of the Acoustical Society of America, 2011, 130(4): Liu Yue, Wang Xiaoting. A speech endpoint detec-
2212–2223. tion algorithm based on fractal in short-term frequency
[5] Johansson A T, White P R. An adaptive filter-based domain[J]. Microelectronics & Computer, 2015, 32(9):
method for robust, automatic detection and frequency es- 81–84, 89.
timation of whistles[J]. The Journal of the Acoustical So- [13] 郑艳, 高爽. 基于自适应门限的分形维数语音端点检测 [J]. 东
ciety of America, 2011, 130(2): 893–903. 北大学学报 (自然科学版), 2020, 41(1): 7–11.
[6] 孙馨喆, 文立, 杨武夷, 等. 基于时频图像处理的宽吻海豚声 Zheng Yan, Gao Shuang. Speech endpoint detection based
通讯信号自动检测方法 [J]. 南京大学学报 (自然科学), 2015, on fractal dimension with adaptive threshold[J]. Journal
51(S1): 16–20. of Northeastern University (Natural Science), 2020, 41(1):
Sun Xinzhe, Wen Li, Yang Wuyi, et al. Detection method 7–11.
for whistles of bottlenose dolphin(Tursiops truncatus) [14] Pitsikalis V, Maragos P. Analysis and classification of
based on spectrogram processing[J]. Journal of Nanjing speech signals by generalized fractal dimension features[J].
University Natural Science, 2015, 51(S1): 16–20. Speech Communication, 2009, 51(12): 1206–1223.
[7] Kirsebom O S, Frazao F, Simard Y, et al. Performance of [15] Baljekar P N, Patil H A. A comparison of waveform frac-
a deep neural network at detecting North Atlantic right tal dimension techniques for voice pathology classifica-
whale upcalls[J]. The Journal of the Acoustical Society of tion[C]// IEEE. IEEE, 2012: 4461–4464.
America, 2020, 147(4): 2636–2646. [16] Lebien J G, Ioup J W. Species-level classification of
[8] Ibrahim A K, Zhuang H Q, Chérubin L M, et al. A mul- beaked whale echolocation signals detected in the north-
timodel deep learning algorithm to detect North Atlantic ern Gulf of Mexico[J]. The Journal of the Acoustical So-
right whale up-calls[J]. The Journal of the Acoustical So- ciety of America, 2018, 144(1): 387–396.
ciety of America, 2021, 150(2): 1264–1264. [17] 贾亮, 尹伊, 杨慧超. 基于分形维数的带噪语音端点检测 [J].
[9] Qiao G, Li L, Liu S Z, et al. Automated classification 沈阳航空航天大学学报, 2017, 34(5): 63–67.
of dolphin whistles based on the convolutional neural net- Jia Liang, Yin Yi, Yang Huichao. Endpoint detection
work[J]. The Journal of the Acoustical Society of America, of noisy speech based on fractal dimension[J]. Journal of
2019, 146(4): 2984. Shenyang Aerospace University, 2017, 34(5): 63–67.
[10] Watkins W. Watkins marine mammal sound database [18] Ye T, Ji W, Wang Z, et al. Fuzzy clustering and
[DB/OL]. [2021-12-22]. https://cis.whoi.edu/science/B/ Bayesian information criterion based threshold estima-
whalesounds/index.cfm. tion for robust voice activity detection[C]// IEEE Interna-
[11] 陈建安. 分形维数的定义及测定方法 [J]. 电子科技, 1999(4): tional Conference on Acoustics. IEEE, 2003: 1444–1447.
44–46.