{"title":"轻量级、多扬声器、多语言 Indic 文本到语音技术","authors":"Abhayjeet Singh;Amala Nagireddi;Anjali Jayakumar;Deekshitha G;Jesuraja Bandekar;Roopa R;Sandhya Badiger;Sathvik Udupa;Saurabh Kumar;Prasanta Kumar Ghosh;Hema A Murthy;Heiga Zen;Pranaw Kumar;Kamal Kant;Amol Bole;Bira Chandra Singh;Keiichi Tokuda;Mark Hasegawa-Johnson;Philipp Olbrich","doi":"10.1109/OJSP.2024.3379092","DOIUrl":null,"url":null,"abstract":"The Lightweight, Multi-speaker, Multi-lingual Indic Text-to-Speech (LIMMITS'23) challenge is organized as part of the ICASSP 2023 Signal Processing Grand Challenge. LIMMITS'23 aims at the development of a lightweight, multi-speaker, multi-lingual Text to Speech (TTS) model using datasets in Marathi, Hindi, and Telugu, with at least 40 hours of data released for each of the male and female voice artists in each language. The challenge encourages the advancement of TTS in Indian Languages as well as the development of techniques involved in TTS data selection and model compression. The 3 tracks of LIMMITS'23 have provided an opportunity for various researchers and practitioners around the world to explore the state-of-the-art techniques in TTS research.","PeriodicalId":73300,"journal":{"name":"IEEE open journal of signal processing","volume":"5 ","pages":"790-798"},"PeriodicalIF":2.9000,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10479171","citationCount":"0","resultStr":"{\"title\":\"Lightweight, Multi-Speaker, Multi-Lingual Indic Text-to-Speech\",\"authors\":\"Abhayjeet Singh;Amala Nagireddi;Anjali Jayakumar;Deekshitha G;Jesuraja Bandekar;Roopa R;Sandhya Badiger;Sathvik Udupa;Saurabh Kumar;Prasanta Kumar Ghosh;Hema A Murthy;Heiga Zen;Pranaw Kumar;Kamal Kant;Amol Bole;Bira Chandra Singh;Keiichi Tokuda;Mark Hasegawa-Johnson;Philipp Olbrich\",\"doi\":\"10.1109/OJSP.2024.3379092\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Lightweight, Multi-speaker, Multi-lingual Indic Text-to-Speech (LIMMITS'23) challenge is organized as part of the ICASSP 2023 Signal Processing Grand Challenge. LIMMITS'23 aims at the development of a lightweight, multi-speaker, multi-lingual Text to Speech (TTS) model using datasets in Marathi, Hindi, and Telugu, with at least 40 hours of data released for each of the male and female voice artists in each language. The challenge encourages the advancement of TTS in Indian Languages as well as the development of techniques involved in TTS data selection and model compression. The 3 tracks of LIMMITS'23 have provided an opportunity for various researchers and practitioners around the world to explore the state-of-the-art techniques in TTS research.\",\"PeriodicalId\":73300,\"journal\":{\"name\":\"IEEE open journal of signal processing\",\"volume\":\"5 \",\"pages\":\"790-798\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10479171\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE open journal of signal processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10479171/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE open journal of signal processing","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10479171/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
The Lightweight, Multi-speaker, Multi-lingual Indic Text-to-Speech (LIMMITS'23) challenge is organized as part of the ICASSP 2023 Signal Processing Grand Challenge. LIMMITS'23 aims at the development of a lightweight, multi-speaker, multi-lingual Text to Speech (TTS) model using datasets in Marathi, Hindi, and Telugu, with at least 40 hours of data released for each of the male and female voice artists in each language. The challenge encourages the advancement of TTS in Indian Languages as well as the development of techniques involved in TTS data selection and model compression. The 3 tracks of LIMMITS'23 have provided an opportunity for various researchers and practitioners around the world to explore the state-of-the-art techniques in TTS research.
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