CLJan 15, 2016
Towards Turkish ASR: Anatomy of a rule-based Turkish g2p
arXiv:1601.03783v11 citations
Originality Synthesis-oriented
AI Analysis
This work addresses a domain-specific need for Turkish automatic speech recognition, but it is incremental as it applies an existing rule-based method to a new language.
The paper tackled the problem of converting Turkish text to phonemes by developing a rule-based grapheme-to-phoneme system that outputs multiple pronunciations with stress positions, but no concrete performance numbers were provided.
This paper describes the architecture and implementation of a rule-based grapheme to phoneme converter for Turkish. The system accepts surface form as input, outputs SAMPA mapping of the all parallel pronounciations according to the morphological analysis together with stress positions. The system has been implemented in Python