圈养瓶鼻海豚通讯信号分析及融合分类方法

针对圈养条件下瓶鼻海豚通讯信号（whistle）分类时混叠大量回声定位信号（click）导致分类正确率降低的问题,提出了一种基于机器学习的融合分类方法。分别提取whistle信号的时频分布特征训练随机森林分类器,梅尔时频图特征训练卷积神经网络分类器,在此基础上设计融合判决器对混叠whistle信号进行分类识别。对圈养海豚声信号采集实验数据的分类识别结果表明,融合分类方法具有更好的分类性能,对混叠whistle信号分类正确率大于94%,优于时频分布特征分类器和梅尔时频图特征分类器,能够提高混叠信号的分类能力。     

圈养宽吻海豚自由游动状态和训练期间通讯信号比较研究

根据频率特性对圈养宽吻海豚(Tursiops truncatus)在自由游动和训练两种实验条件下的声通讯信号进行分类,并利用双尾t检验统计分析方法对两种条件下的信号声谱参数进行统计比较。结果显示,宽吻海豚在自由状态下通讯信号的种类多并以正弦型为主,而训练期间的通讯信号则大多数为上扫频类。此外,统计分析表明起始频率不能反映这两种状态的不同(p=0.22)。结束频率、最小频率、最大频率、频率变化量、拐点数、环形数、阶数、波形数和周期等则显示了两种状态显著的差异性(p＜0.05)。结果为今后海豚声行为研究提供一定的科学参考和基础。     

谐波显著度的基频提取方法

我们提出的谐波显著度的基频提取方法,目的是从语音信号中自动获取人声基频,该方法利用抑制因子计算出基频的谐波显著度谱,对各次谐波显著度加权求和之后进行基频轨迹跟踪确定语音的基频序列。在TIMIT掺噪数据集和音乐信息检索评测2005主旋律数据集上,谐波显著度方法的准确率分别达到了88.5%和73.3%,使倍频、半频错误相对降低了80%。实验表明,基于谐波显著度的基频提取方法增强了系统的抗噪性能以及抗倍半频错误的能力。     

印太瓶鼻海豚(Tursiops aduncus)通讯声信号分类及特征参数的环境差异性分析

通过长期记录室内水池环境下两只印太瓶鼻海豚通讯信号,并与海湾自然环境下同样的两只海豚所发出的通讯信号进行比较分析,从信号类型、声谱特征等方面研究生活环境变化下瓶鼻海豚通讯信号的差异性。结果表明,生活环境的差异,会改变瓶鼻海豚通讯信号。海湾自然环境下,瓶鼻海豚通讯信号以正弦型信号为主;而室内水池环境下,上扫型信号比例明显增多,而正弦型信号减少。两种环境下,瓶鼻海豚通讯信号在持续时间、拐点数、起始频率、结束频率、最小频率、最大频率等存在显著性差异(p<0.05),但信号的频率变化量相近(p=0.29)。结果为提高海豚通讯信号认知和增强海豚生物行为研究提供一定的科学参考,同时也为仿生隐蔽通信提供技术支撑。      

宽吻海豚Click信号的时频滤波检测方法

针对宽吻海豚Click信号检测提出了一种在信号时频图中基于Gabor滤波器的检测方法。该方法首先对声信号进行分段处理,计算每一段信号的时频图;然后设计Gabor滤波器,提取时频图中垂直方向的线条;对Gabor滤波处理后的时频图进行自适应阈值处理,提取时频图中能量较强的区域;最后通过连通域分析确定Click信号的位置.仿真合成不同信噪比的测试信号,本文算法在Click信号和背景噪声平均功率比为15 dB的情况下,Click信号的找全率达到了99%,错误率为0%;对实际采集的声信号进行Click信号检测,找全率为100%。本文方法预期为海豚观测和海豚生物学行为的研究提供一定的技术支持。     

在噪声的背景中提取语言信息

本文介绍了从噪声的背景中提取语言信号的频谱减方法、自相关方法和线性滤波方法及其对信噪比从+6dB到-6dB的汉语元音、词句和语句进行处理的结果。经过处理后信噪比均可提高6dB左右,但语言的可懂度没有明显改善。本文还对几种提取基频的方法,在噪声背景中提取语言基频的效果作了比较。     

预分浊音型的LPC基音提取法

本文介绍一种预分浊音型的LPC基音提取算法,对语言信号先用线性预测系数a₀和a₁的差值分出浊音区,然后只对浊音部分进行基音提取。提取基频时,数据率减半,用LPC的自相关方法产生8个预测系数的倒滤波器,倒滤波后的误差信号,用平均幅差函数（AMDF）方法提取基频,再线性插值,最后用非线性平滑滤波,并将所得结果和一个半自动的精确算法,以及简化倒滤波（SIFT）算法进行比较,说明我们提出的算法,对背景噪声40dB以下的连续语言是准确有效的。它避免了清音和无声间隙区的音调计算,且浊音和清音的判别比较准确。     

对超声DOPPLER声谱图进行分类决策的两种方法

本文介绍了两种对超声多普勒血流声谱图进行了波形自动分类法决策的方法，方法一与统计得到的标准波形相比，按适当判据进行自动分类，方法二，送入训练的人工神经网络进行自动分类，待分类波形由计算多普勒信号的最大频率提取声谱包络并经分段，平均和归一化等处理得以，文中给出了计算机模拟的结果。     

分形维数海豚哨声信号检测方法

针对海豚哨声信号自动检测的问题,提出一种基于分形维数的自适应阈值海豚哨声信号检测方法。对待检测声信号计算盒分形维数,根据得到的盒分形维数特征值,通过模糊C均值聚类自适应确定检测阈值,实现海豚哨声信号的自动检测。文中对水池录制的海豚声信号进行了数据分析,利用哨声信号盒分形维数对哨声信号段与非信号段进行检测,并与基于谱熵的方法进行对比,获得了较高的检测率以及较低的虚警率,可以适用于海豚哨声信号的自动检测与分割。     

三维测量中一种新的自适应窗口傅里叶相位提取法

针对多尺度窗口傅里叶变换中,窗口尺寸的自适应选取及提取基频时的频谱混叠等问题,提出基于希尔伯特-黄变换(HHT)的自适应窗口傅里叶相位提取法。对变形条纹信号进行HHT后,通过谱分析,自适应确定能够准确描述条纹信号变化情况的瞬时频率及条纹图的背景分量。根据所得的瞬时频率,给出自适应定位条纹信号局部平稳区域的步骤,进而确定窗口尺寸。不需额外计算,可有效去除背景分量以减少基频提取过程中零频频谱的干扰。与现有的用最大脊法确定窗口尺寸的方法相比,本方法不受被测相位必须线性逼近且变化缓慢的前提约束。实验证明本方法有效、可行,且对测量携带陡峭边缘或面形复杂的物体也能进行较为精确有效的测量。     

A method for classifying whistles of bottlenose dolphin(Tursiops truncates) based on syntactic pattern reorganization

A method based on syntactic pattern recognition was presented to automatically classify whistles of bottlenose dolphin.Dolphin whistles have typically been characterized in terms of their instantaneous frequency as a function of time,which is also known as "whistle contour".The frequency variation features of a whistle were extracted according to its contour.Then,the frequency variation features were used for learning grammatical patterns.A whistle was classified according to grammatical pattern of its frequency variation features.The experimental results showed that the classification accuracy of the proposed method was 95%.The method can provide technical support for acoustic study of dolphins' biological behavior.     

Synthesis and modification of the whistles of the bottlenose dolphin, Tursiops truncatus

A signal-processing algorithm was developed to analyze harmonic frequency-modulated sounds, to modify the parameters of the analyzed signal, and to synthesize a new analytically specified signal that resembles the original signal in specified features. This algorithm was used with dolphin whistles, a frequency-modulated harmonic signal that has typically been described in terms of its contour, or pattern of modulation of the fundamental frequency. In order to test whether other features may also be salient to dolphins, the whistle analysis calculates the energies at the harmonics as well as the fundamental frequency of the whistle. The modification part of the algorithm can set all of these energies to a constant, can shift the whistle frequency, and can expand or compress the time base or the frequency of the whistle. The synthesis part of the algorithm then synthesizes a waveform based upon the energies and frequencies of the fundamental and first two harmonics. These synthetic whistles will be useful for evaluating what acoustic features dolphins use in discriminating different whistles.     

Geographic variations in the whistles of spinner dolphins (Stenella longirostris) of the Main Hawai'ian Islands

Geographic variations in the whistles of Hawai'ian spinner dolphins are discussed by comparing 27 spinner dolphin pods recorded in waters off the Islands of Kaua'i, O'ahu, Lana'i, and Hawai'i. Three different behavioral states, the number of dolphins observed in each pod, and ten parameters extracted from each whistle contour were considered by using clustering and discriminant function analyses. The results suggest that spinner dolphin pods in the Main Hawai'ian Islands share characteristics in approximately 48% of their whistles. Spinner dolphin pods had similar whistle parameters regardless of the island, location, and date when they were sampled and the dolphins' behavioral state and pod size. The term "whistle-specific subgroup" (WSS) was used to designate whistle groups with similar whistles parameters (which could have been produced in part by the same dolphins). The emission rate of whistles was higher when spinner dolphins were socializing than when they were traveling or resting, suggesting that whistles are mainly used during close-range interactions. Spinner dolphins also seem to vary whistle duration according to their general behavioral state. Whistle duration and the number of turns and steps of a whistle may be more important in delivering information at the individual level than whistle frequency parameters.     

Captive dolphins,Tursiops truncatus,develop signature whistles that match acoustic features of human-made model sounds

This paper presents a cross-sectional study testing whether dolphins that are born in aquarium pools where they hear trainers' whistles develop whistles that are less frequency modulated than those of wild dolphins. Ten pairs of captive and wild dolphins were matched for age and sex. Twenty whistles were sampled from each dolphin. Several traditional acoustic features (total duration, duration minus any silent periods, etc.) were measured for each whistle, in addition to newly defined flatness parameters: total flatness ratio (percentage of whistle scored as unmodulated), and contiguous flatness ratio (duration of longest flat segment divided by total duration). The durations of wild dolphin whistles were found to be significantly longer, and the captive dolphins had whistles that were less frequency modulated and more like the trainers' whistles. Using a standard t-test, the captive dolphin had a significantly higher total flatness ratio in 9/10 matched pairs, and in 8/10 pairs the captive dolphin had significantly higher contiguous flatness ratios. These results suggest that captive-born dolphins can incorporate features of artificial acoustic models made by humans into their signature whistles.     

An adaptive filter-based method for robust, automatic detection and frequency estimation of whistles

This paper proposes an adaptive filter-based method for detection and frequency estimation of whistle calls, such as the calls of birds and marine mammals, which are typically analyzed in the time-frequency domain using a spectrogram. The approach taken here is based on adaptive notch filtering, which is an established technique for frequency tracking. For application to automatic whistle processing, methods for detection and improved frequency tracking through frequency crossings as well as interfering transients are developed and coupled to the frequency tracker. Background noise estimation and compensation is accomplished using order statistics and pre-whitening. Using simulated signals as well as recorded calls of marine mammals and a human whistled speech utterance, it is shown that the proposed method can detect more simultaneous whistles than two competing spectrogram-based methods while not reporting any false alarms on the example datasets. In one example, it extracts complete 1.4 and 1.8 s bottlenose dolphin whistles successfully through frequency crossings. The method performs detection and estimates frequency tracks even at high sweep rates. The algorithm is also shown to be effective on human whistled utterances.     

Who is whistling? Localizing and identifying phonating dolphins in captivity

Acoustic communication through whistles is well developed in dolphins. However, little is known on how dolphins are using whistles because localizing the sound source is not an easy task. In the present study, the hyperbola method was used to localize the sound source using a two-hydrophone array. A combined visual and acoustic method was used to determine the identity of the whistling dolphin. In an aquarium in Mexico City where two adult bottlenose dolphins were housed we recorded 946 whistles during 22 days. We found that a dolphin was located along the calculated hyperbola for 72.9% of the whistles, but only for 60.3% of the whistles could we determine the identity of the whistling dolphin. However, sometimes it was possible to use other cues to identify the whistling dolphin. It could be the animal that performed a behavior named “observation” at the time whistling occurred or, when a whistle was only recorded on one channel, the whistling dolphin could be the animal located closest to the hydrophone that captured the whistle. Using these cues, 15.4% of the whistles were further ascribed to either dolphin to obtain an overall identification efficiency of 75.7%. Our results show that a very simple and inexpensive acoustic setup can lead to a reasonable number of identifications of the captive whistling dolphin: this is the first study to report such a high rate of whistles identified to the free swimming, captive dolphin that produced them. Therefore, we have a data set with which we can investigate how dolphins are using whistles. This method can be applied in other aquaria where a small number of dolphins is housed; though, the actual efficiency of this method will depend on how often dolphins spend time next to each other and on the reverberation conditions of the pool.     

The freshwater dolphin Inia geoffrensis geoffrensis produces high frequency whistles

Because whistles are most commonly associated with social delphinids, they have been largely overlooked, ignored, or presumed absent, in solitary freshwater dolphin species. Whistle production in the freshwater dolphin, the boto (Inia geoffrensis geoffrensis), has been controversial. Because of its sympatry with tucuxi dolphins (Sotalia fluviatilis), a whistling species, some presume tucuxi whistles might have been erroneously assigned to the boto. Using a broadband recording system, we recorded over 100 whistles from boto dolphins in the Yasunf River, Ecuador, where the tucuxi dolphins are absent. Our results therefore provide conclusive evidence for whistle production in Inia geoffrensis geoffrensis. Furthermore, boto whistles are significantly different from tucuxi whistles recorded in nearby rivers. The Ecuadorian boto whistle has a significantly greater frequency range (5.30-48.10 kHz) than previously reported in other populations (Peru and Colombia) that were recorded with more bandwidth limited equipment. In addition, the top frequency and the range are greater than in any other toothed whale species recorded to date. Whistle production was higher during resting activities, alone or in the presence of other animals. The confirmation of whistles in the boto has important implications for the evolution of whistles in Cetacea and their association with sociality.     

The whistles of Hawaiian spinner dolphins

The characteristics of the whistles of Hawaiian spinner dolphins (Stenella longirostris) are considered by examining concurrently the whistle repertoire (whistle types) and the frequency of occurrence of each whistle type (whistle usage). Whistles were recorded off six islands in the Hawaiian Archipelago. In this study Hawaiian spinner dolphins emitted frequency modulated whistles that often sweep up in frequency (47% of the whistles were upsweeps). The frequency span of the fundamental component was mainly between 2 and 22 kHz (about 94% of the whistles) with an average mid-frequency of 12.9 kHz. The duration of spinner whistles was relatively short, mainly within a span of 0.05 to 1.28 s (about 94% of the whistles) with an average value of 0.49 s. The average maximum frequency of 15.9 kHz obtained by this study is consistent with the body length versus maximum frequency relationship obtained by Wang et al. (1995a) when using spinner dolphin adult body length measurements. When comparing the average values of whistle parameters obtained by this and other studies in the Island of Hawaii, statistically significant differences were found between studies. The reasons for these differences are not obvious. Some possibilities include differences in the upper frequency limit of the recording systems, different spinner groups being recorded, and observer differences in viewing spectrograms. Standardization in recording and analysis procedure is clearly needed.     

Killer whales (Orcinus orca) produce ultrasonic whistles

This study reports that killer whales, the largest dolphin, produce whistles with the highest fundamental frequencies ever reported in a delphinid. Using wide-band acoustic sampling from both animal-attached (Dtag) and remotely deployed hydrophone arrays, ultrasonic whistles were detected in three Northeast Atlantic populations but not in two Northeast Pacific populations. These results are inconsistent with analyses suggesting a correlation of maximum frequency of whistles with body size in delphinids, indicate substantial intraspecific variation in whistle production in killer whales, and highlight the importance of appropriate acoustic sampling techniques when conducting comparative analyses of sound repertoires.