Requirements and Motivations of Low-Resource Speech Synthesis for Language Revitalization
Aidan Pine | Dan Wells | Nathan Brinklow | Patrick Littell | Korin Richmond
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
This paper describes the motivation and development of speech synthesis systems for the purposes of language revitalization. By building speech synthesis systems for three Indigenous languages spoken in Canada, Kanien’kéha, Gitksan & SENĆOŦEN, we re-evaluate the question of how much data is required to build low-resource speech synthesis systems featuring state-of-the-art neural models. For example, preliminary results with English data show that a FastSpeech2 model trained with 1 hour of training data can produce speech with comparable naturalness to a Tacotron2 model trained with 10 hours of data. Finally, we motivate future research in evaluation and classroom integration in the field of speech synthesis for language revitalization.
Detecting Subject Boundaries Within Text: A Language Independent Statistical Approach
Korin Richmond | Andrew Smith | Einat Amitay
Second Conference on Empirical Methods in Natural Language Processing
- Andrew Smith 1
- Einat Amitay 1
- Aidan Pine 1
- Dan Wells 1
- Nathan Brinklow 1
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