  Modern speech synthesis uses neural vocoders to model raw waveform samples
directly. This increased versatility has expanded the scope of vocoders from
speech to other domains, such as music. We address another interesting domain
of bio-acoustics. We provide initial comparative analysis-resynthesis
experiments of birdsong using traditional (WORLD) and two neural (WaveNet
autoencoder, parallel WaveGAN) vocoders. Our subjective results indicate no
difference in the three vocoders in terms of species discrimination (ABX test).
Nonetheless, the WORLD vocoder samples were rated higher in terms of retaining
bird-like qualities (MOS test). All vocoders faced issues with pitch and
voicing. Our results indicate some of the challenges in processing low-quality
wildlife audio data.
