  This study reports our efforts to improve automatic recognition of
suprasegmentals by fine-tuning wav2vec 2.0 with CTC, a method that has been
successful in automatic speech recognition. We demonstrate that the method can
improve the state-of-the-art on automatic recognition of syllables, tones, and
pitch accents. Utilizing segmental information, by employing tonal finals or
tonal syllables as recognition units, can significantly improve Mandarin tone
recognition. Language models are helpful when tonal syllables are used as
recognition units, but not helpful when tones are recognition units. Finally,
Mandarin tone recognition can benefit from English phoneme recognition by
combining the two tasks in fine-tuning wav2vec 2.0.
