Papers by Haris Bin Zia

2 papers
PronouncUR: An Urdu Pronunciation Lexicon Generator (L18-1)

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Challenge: acoustic modeling, large text data and a pronunciation lexicon are the bottlenecks for speech recognition systems for resource scarce languages.
Approach: They propose a grapheme-to-phoneme conversion tool that generates a pronunciation lexicon from a list of Urdu words.
Outcome: The proposed tool predicts pronunciation of words using a LSTM-based model trained on a handcrafted expert lexicon of around 39,000 words and shows an accuracy of 64% upon internal evaluation.
Urdu Word Segmentation using Conditional Random Fields (CRFs) (C18-1)

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Challenge: Urdu is amongst languages for which word segmentation is a complex task as it exhibits space omission and space insertion issues.
Approach: They propose a word segmentation system for Urdu which uses a Conditional Random Field sequence modeler with orthographic, linguistic and morphological features.
Outcome: The proposed system achieves an F1 score for word boundary identification and 0.85 for sub-word boundary identification tasks.

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