A Unified Framework for Collecting Text-to-Speech Synthesis Datasets for 22 Indian Languages

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Main Authors: Sathiyamoorthy, Sujitha, Mohana, N, Prakash, Anusha, Murthy, Hema A
Format: Preprint
Published: 2024
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author Sathiyamoorthy, Sujitha
Mohana, N
Prakash, Anusha
Murthy, Hema A
author_facet Sathiyamoorthy, Sujitha
Mohana, N
Prakash, Anusha
Murthy, Hema A
contents The performance of a text-to-speech (TTS) synthesis model depends on various factors, of which the quality of the training data is of utmost importance. Millions of data are collected around the globe for various languages, but resources for Indian languages are few. Although there are many efforts involved in data collection, a common set of protocols for data collection becomes necessary for building TTS systems in Indian languages primarily because of the need for a uniform development of TTS systems across languages. In this paper, we present our learnings on data collection efforts' for Indic languages over 15 years. These databases have been used in unit selection synthesis, hidden Markov model based, and end-to-end frameworks, and for generating prosodically rich TTS systems. The most significant feature of the data collected is that data purity enables building high-quality TTS systems with a comparatively small dataset compared to that of European/Chinese languages.
format Preprint
id arxiv_https___arxiv_org_abs_2410_14197
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Unified Framework for Collecting Text-to-Speech Synthesis Datasets for 22 Indian Languages
Sathiyamoorthy, Sujitha
Mohana, N
Prakash, Anusha
Murthy, Hema A
Audio and Speech Processing
The performance of a text-to-speech (TTS) synthesis model depends on various factors, of which the quality of the training data is of utmost importance. Millions of data are collected around the globe for various languages, but resources for Indian languages are few. Although there are many efforts involved in data collection, a common set of protocols for data collection becomes necessary for building TTS systems in Indian languages primarily because of the need for a uniform development of TTS systems across languages. In this paper, we present our learnings on data collection efforts' for Indic languages over 15 years. These databases have been used in unit selection synthesis, hidden Markov model based, and end-to-end frameworks, and for generating prosodically rich TTS systems. The most significant feature of the data collected is that data purity enables building high-quality TTS systems with a comparatively small dataset compared to that of European/Chinese languages.
title A Unified Framework for Collecting Text-to-Speech Synthesis Datasets for 22 Indian Languages
topic Audio and Speech Processing
url https://arxiv.org/abs/2410.14197