{"title":"TTS - VLSP 2021:迅雷文本转语音系统","authors":"N. Ngoc Anh, Nguyen Tien Thanh, Le Dang Linh","doi":"10.25073/2588-1086/vnucsce.342","DOIUrl":null,"url":null,"abstract":"This paper describes our speech synthesis system participating in the Vietnamese Text-To-Speech track of the 2021 VLSP evaluation campaign. The goal of this challenge is to build a synthetic voice from a provided spontaneous speech corpus in Vietnamese. In this paper, we propose our implementation of FastSpeech2 model on spontaneous speech. We used a special strategy with spontaneous datasets using the TTS system. We present our utilization in generating mel-spectrograms from given texts and then synthesize speech from generated mel-spectrograms using a separately trained vocoder. In evaluation, our team achieved 3.943 mean score in MOS in-domain test, 3.3 in MOS out-domain test, and 85.00% SUS, which indicates the effectiveness of the proposed system.","PeriodicalId":416488,"journal":{"name":"VNU Journal of Science: Computer Science and Communication Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"TTS - VLSP 2021: The Thunder Text-To-Speech System\",\"authors\":\"N. Ngoc Anh, Nguyen Tien Thanh, Le Dang Linh\",\"doi\":\"10.25073/2588-1086/vnucsce.342\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes our speech synthesis system participating in the Vietnamese Text-To-Speech track of the 2021 VLSP evaluation campaign. The goal of this challenge is to build a synthetic voice from a provided spontaneous speech corpus in Vietnamese. In this paper, we propose our implementation of FastSpeech2 model on spontaneous speech. We used a special strategy with spontaneous datasets using the TTS system. We present our utilization in generating mel-spectrograms from given texts and then synthesize speech from generated mel-spectrograms using a separately trained vocoder. In evaluation, our team achieved 3.943 mean score in MOS in-domain test, 3.3 in MOS out-domain test, and 85.00% SUS, which indicates the effectiveness of the proposed system.\",\"PeriodicalId\":416488,\"journal\":{\"name\":\"VNU Journal of Science: Computer Science and Communication Engineering\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"VNU Journal of Science: Computer Science and Communication Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25073/2588-1086/vnucsce.342\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"VNU Journal of Science: Computer Science and Communication Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25073/2588-1086/vnucsce.342","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
TTS - VLSP 2021: The Thunder Text-To-Speech System
This paper describes our speech synthesis system participating in the Vietnamese Text-To-Speech track of the 2021 VLSP evaluation campaign. The goal of this challenge is to build a synthetic voice from a provided spontaneous speech corpus in Vietnamese. In this paper, we propose our implementation of FastSpeech2 model on spontaneous speech. We used a special strategy with spontaneous datasets using the TTS system. We present our utilization in generating mel-spectrograms from given texts and then synthesize speech from generated mel-spectrograms using a separately trained vocoder. In evaluation, our team achieved 3.943 mean score in MOS in-domain test, 3.3 in MOS out-domain test, and 85.00% SUS, which indicates the effectiveness of the proposed system.