A Generative Model of a Pronunciation Lexicon for Hindi
Pramod Pandey, Somnath Roy
TL;DR
This paper presents a generative model for Hindi pronunciation lexicons that automatically produces phoneme and prosodic structure representations, including syllable division and stress, for use in TTS and ASR systems.
Contribution
It introduces a novel model and tool for automatically generating Hindi lexicons with phonetic and prosodic details, enhancing speech system development.
Findings
Successfully generates Hindi lexicons with phoneme and prosodic annotations
Automates syllable division and stress placement in Hindi lexicons
Provides a tool for improved Hindi speech processing applications
Abstract
Voice browser applications in Text-to- Speech (TTS) and Automatic Speech Recognition (ASR) systems crucially depend on a pronunciation lexicon. The present paper describes the model of pronunciation lexicon of Hindi developed to automatically generate the output forms of Hindi at two levels, the <phoneme> and the <PS> (PS, in short for Prosodic Structure). The latter level involves both syllable-division and stress placement. The paper describes the tool developed for generating the two-level outputs of lexica in Hindi.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNatural Language Processing Techniques · Speech Recognition and Synthesis · Music and Audio Processing