![tts voices online tts voices online](https://i.ytimg.com/vi/Z4hqUxb9MmY/hqdefault.jpg)
It has been proved that LRSpeech has the capability to build good quality TTS in the low-resource setting, using multilingual pre-training, knowledge distillation, and importantly the dual transformation between text-to-speech (TTS) and speech recognition (SR).īuilt on top of LRSpeech and the multi-lingual multi-speaker transformer TTS model (called UNI-TTS), we have designed the offline model training pipeline and the online inference pipeline for the low-resource TTS. To handle the challenge, Microsoft researchers have proposed an innovative approach, called LRSpeech, to handle the extremely low-resourced TTS development. In many cases, one major challenge for supporting a new language is that such large volume of data is unavailable or hard to find, causing a language ‘low-resourced’ for TTS model building. This includes collecting tens of hours of language-specific training data, and creating hand-crafted components like text analysis etc. Traditionally, it can easily take more than 10 months to extend TTS service to support a new language due to the extensive language-specific engineering required. With this innovation, we are able to improve the Neural TTS locale development with 10x agility and support the five new languages quickly. In this section, we introduce “ LR-UNI-TTS”, a new Neural TTS production pipeline to create TTS languages where training data is limited, i.e., ‘low-resourced’. The creation of a TTS voice model normally requires a large volume of training data, especially for extending to a new language, where sophisticated language-specific engineering is required. With these updates, Azure TTS service now supports 54 languages/locales with 78 neural voices and 77 standard voices available.īehind the scenes: 10X faster voice building with the low resource setting. Tá an scoil sa mbaile ar oscailt arís inniu.ĭaži tumšās šokolādes gabaliņi dienā ir gandrīz būtiska uztura sastāvdaļa. Pese voodipesu kord nädalas või vähemalt kord kahe nädala järel ning ära unusta pesta ka kardinaid. Hear samples of these voices, or try them with your own text in our demo.įid-diskors tiegħu, is-Segretarju Parlamentari fakkar li dan il-Gvern daħħal numru ta’ liġijiet u inizjattivi li jħarsu lill-annimali.ĭerinti motinystę ir kūrybą išmokau jau po pirmojo vaiko gimimo. These voices are available in public preview in three Azure regions: EastUS, SouthEastAsia and WestEurope.
![tts voices online tts voices online](https://convertspeech.com/img/logow.png)
They are: Grace in Maltese (Malta), Ona in Lithuanian (Lithuania), Anu in Estonian (Estonia), Orla in Irish (Ireland) and Everita in Latvian (Latvia).
![tts voices online tts voices online](https://www.smashingapps.com/wp-content/uploads/2012/06/speechconversion15b.jpg)
At the same time, Neural TTS Container is generally available for customers who want to deploy neural voice models on-prem for specific security requirements.įive new voices and languages are introduced to the Neural TTS portfolio. Today, we are excited to announce that Azure Neural TTS has extended its global support to five new languages: Maltese, Lithuanian, Estonian, Irish and Latvian, in public preview. At the same time, we continue to receive customer requests for more voice choices and more language support globally. Hongdandan, a non-profit organization, is using neural voices in Chinese to make their online books audible for the blind people in China.īy September 2020, we extended Neural TTS to support 49 languages/locales with 68 voices. Swisscom and Poste Italiane are adopting neural voices in French, German and Italian to interact with their customers in the European market. For example, the BBC, Progressive and Motorola Solutions are using Azure Neural TTS to develop conversational interfaces for their voice assistants in English speaking locales. Neural TTS has powered a wide range of scenarios, from audio content creation to natural-sounding voice assistants, for customers from all over the world. Neural Text-to-Speech (Neural TTS), part of Speech in Azure Cognitive Services, enables you to convert text to lifelike speech for more natural user interactions. This post is co-authored with Xianghao Tang, Lihui Wang, Jun-Wei Gan, Gang Wang, Garfield He, Xu Tan and Sheng Zhao