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Phones, the segmental units of the International Phonetic Alphabet (IPA), areused for lexical distinctions in most human languages; Tones, thesuprasegmental units of the IPA, are used in perhaps 70%. Many previous studieshave explored cross-lingual adaptation of automatic speech recognition (ASR)phone models, but few have explored the multilingual and cross-lingual transferof synchronization between phones and tones. In this paper, we test fourConnectionist Temporal Classification (CTC)-based acoustic models, differing inthe degree of synchrony they impose between phones and tones. Models aretrained and tested multilingually in three languages, then adapted and testedcross-lingually in a fourth. Both synchronous and asynchronous models areeffective in both multilingual and cross-lingual settings. Synchronous modelsachieve lower error rate in the joint phone+tone tier, but asynchronoustraining results in lower tone error rate.

Autosegmental Neural Nets: Should Phones and Tones be Synchronous or Asynchronous?