An automatic syllabifier is an algorithm that takes words and produces a linguistically correct breakdown of the word into syllables. When working with language data, especially in audio, it can be very useful to break utterances down by syllable, because syllables represent a unit of sound that is below the word level but above the phoneme level, which is useful for identifying properties of sound like stress.
Syllabifying IPA transcribed text is not very challenging. Look at this link for example, an automatic syllabification algorithm by Penn University based on phoneme strings. This is done by identifying the nucleus center of the syllable in the IPA and then predicting the correct boundary of the syllable around it. Using a linguistic assumption called the maximum onset principle , we pick the largest onset such that the string of phonemes contained in the onset does not violate any of the phonetic restrictions of the language. These rules an be inferred via a distribution obtained from a corpus. Despite being an important aspect of audio analysis however, the availability of direct audio to syllable algorithms is limited. There are some algorithms that apply spectral analysis on the input to identify syllable boundaries, but these require advanced mathematics to use and have not been used since the 1900s. A syllabification can be obtained if you have a proper alignment between the text and audio, so a direct analysis of audio is not needed. This has the advantage of being more robust to the quirks of the sound, since mapping audio signals to phonemes is easier and a much more actively studied area of research than mapping audio signals to syllables. This application aims to gather these ideas and provide a convenient program that can automatically syllabify speech. Currently, it can produce automatic syllabifications for English text, but I am currently working to add additional support as mentioned above, including for German and Arabic!