AI Chat AI Image Generator AI Video Text to Speech

A Generative Model of a Pronunciation Lexicon for Hindi

05/06/2017

∙

by Pramod Pandey, et al.

∙

∙

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.

Pramod Pandey
1 publication
Somnath Roy
7 publications

page 1

page 2

page 3

page 4

research

∙ 03/16/2021

Fast Development of ASR in African Languages using Self Supervised Speech Representation Learning

This paper describes the results of an informal collaboration launched d...

0 Jama Hussein Mohamud, et al. ∙

research

∙ 01/30/2020

BUT Opensat 2019 Speech Recognition System

The paper describes the BUT Automatic Speech Recognition (ASR) systems s...

0 Martin Karafiat, et al. ∙

research

∙ 01/05/2022

Strategies of Effective Digitization of Commentaries and Sub-commentaries: Towards the Construction of Textual History

This paper describes additional aspects of a digital tool called the 'Te...

2 Diptesh Kanojia, et al. ∙

research

∙ 12/13/2016

Evaluating Automatic Speech Recognition Systems in Comparison With Human Perception Results Using Distinctive Feature Measures

This paper describes methods for evaluating automatic speech recognition...

0 Xiang Kong, et al. ∙

research

∙ 10/20/2019

Neuro-SERKET: Development of Integrative Cognitive System through the Composition of Deep Probabilistic Generative Models

This paper describes a framework for the development of an integrative c...

0 Tadahiro Taniguchi, et al. ∙

research

∙ 01/20/2021

The JHU ASR System for VOiCES from a Distance Challenge 2019

This paper describes the system developed by the JHU team for automatic ...

0 Yiming Wang, et al. ∙

research

∙ 09/19/2017

A Recorded Debating Dataset

This paper describes an audio and textual dataset of debating speeches, ...

0 Shachar Mirkin, et al. ∙