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您的检索式：作者名="Shengjing SONG"
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| 1 | Bats adjust temporal parameters of echolocation pulses but not those of communication calls in response to traffic noise显示文摘Many studies based on acute short-term noise exposure have demonstrated that animals can adjust their vocalizations in response to ambient noise.However,the effects of chronic noise over a relatively long time scale of multiple days remain largely unclear.Bats rely mainly on acoustic signals for perception of environmental and social communication.Nearly all previous studies on noise-induced vocal adjustments have focused on echolocation pulse sounds.Relatively little is known regarding the effects of noise on social communication calls.Here,we examined the dynamic changes in the temporal parameters of echolocation and communication vocalizations of Vespertilio sinensis when exposed to traffic noise over multiple days.We found that the bats started to modify their echolocation vocalizations on the fourth day of noise exposure,with an increase of 42-91%in the total number of pulse sequences per day.Under noisy conditions,the number of pulses within a pulse sequence decreased by an average of 17.2%,resulting in a significantly slower number of pulses/sequence(P<0.001).However,there was little change in the duration of a pulse sequence.These parameters were not significantly adjusted in most communication vocalizations under the noise condition(all P>0.05),except that the duration decreased and the number of syllables/sequences increased in 1 type of communicative vocalization(P<0.05).This study suggests that bats routinely adjust temporal parameters of echolocation but rarely of communication vocalizations in response to noise condition. | Shengjing SONG Aiqing LIN Tinglei JIANG Xin ZHAO Walter METZNER Jiang FENG | 2019 | Integrative Zoology2019，14，6： | 1 |
| 2 | Separating overlapping bat calls with a bi-directional long short-term memory network显示文摘Acquiring clear acoustic signals is critical for the analysis of animal vocalizations.Bioacoustics studies commonly face the problem of overlapping signals,which can impede the structural identification of vocal units,but there is currently no satisfactory solution.This study presents a bi-directional long short-term memory network to separate overlapping echolocation-communication calls of 6 different bat species and reconstruct waveforms.The separation quality was evaluated using 7 temporal-spectrum parameters.All the echolocation pulses and syllables of communication calls in the overlapping signals were separated and parameter comparisons showed no significant difference and negligible deviation between the extracted and original calls.Clustering analysis was conducted with separated echolocation calls from each bat species to provide an example of practical application of the separated and reconstructed calls.The result of clustering analysis showed high corrected rand index(82.79%),suggesting the reconstructed waveforms could be reliably used for species classification.These results demonstrate a convenient and automated approach for separating overlapping calls.The study extends the application of deep neural networks to separate overlapping animal sounds. | Kangkang ZHANG Tong LIU Shengjing SONG Xin ZHAO Shijun SUN Walter METZNER Jiang FENG Ying LIU | 2022 | Integrative Zoology2022，17，5： | 0 |
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