What is text-to-speech?
In this overview, you learn about the benefits and capabilities of the text-to-speech feature of the Speech service, which is part of Azure Cognitive Services.
Text-to-speech enables your applications, tools, or devices to convert text into humanlike synthesized speech. The text-to-speech capability is also known as speech synthesis. Use humanlike prebuilt neural voices out of the box, or create a custom neural voice that's unique to your product or brand. For a full list of supported voices, languages, and locales, see Language and voice support for the Speech service.
Text-to-speech includes the following features:
|Prebuilt neural voice (called Neural on the pricing page)||Highly natural out-of-the-box voices. Create an Azure account and Speech service subscription, and then use the Speech SDK or visit the Speech Studio portal and select prebuilt neural voices to get started. Check the pricing details.||Check the voice samples and determine the right voice for your business needs.|
More about neural text-to-speech features
The text-to-speech feature of the Speech service on Azure has been fully upgraded to the neural text-to-speech engine. This engine uses deep neural networks to make the voices of computers nearly indistinguishable from the recordings of people. With the clear articulation of words, neural text-to-speech significantly reduces listening fatigue when users interact with AI systems.
The patterns of stress and intonation in spoken language are called prosody. Traditional text-to-speech systems break down prosody into separate linguistic analysis and acoustic prediction steps that are governed by independent models. That can result in muffled, buzzy voice synthesis.
Here's more information about neural text-to-speech features in the Speech service, and how they overcome the limits of traditional text-to-speech systems:
- Real-time speech synthesis: Use the Speech SDK or REST API to convert text-to-speech by using prebuilt neural voices.
Prebuilt neural voices: Microsoft neural text-to-speech capability uses deep neural networks to overcome the limits of traditional speech synthesis with regard to stress and intonation in spoken language. Prosody prediction and voice synthesis happen simultaneously, which results in more fluid and natural-sounding outputs. Each prebuilt neural voice model is available at 24kHz and high-fidelity 48kHz. You can use neural voices to:
- Make interactions with chatbots and voice assistants more natural and engaging.
- Convert digital texts such as e-books into audiobooks.
- Enhance in-car navigation systems.
For a full list of platform neural voices, see Language and voice support for the Speech service.
Fine-tuning text-to-speech output with SSML: Speech Synthesis Markup Language (SSML) is an XML-based markup language that's used to customize text-to-speech outputs. With SSML, you can adjust pitch, add pauses, improve pronunciation, change speaking rate, adjust volume, and attribute multiple voices to a single document.
You can use SSML to define your own lexicons or switch to different speaking styles. With the multilingual voices, you can also adjust the speaking languages via SSML. To fine-tune the voice output for your scenario, see Improve synthesis with Speech Synthesis Markup Language and Speech synthesis with the Audio Content Creation tool.
Visemes: Visemes are the key poses in observed speech, including the position of the lips, jaw, and tongue in producing a particular phoneme. Visemes have a strong correlation with voices and phonemes.
By using viseme events in Speech SDK, you can generate facial animation data. This data can be used to animate faces in lip-reading communication, education, entertainment, and customer service. Viseme is currently supported only for the
en-US(US English) neural voices.
We plan to retire the traditional/standard voices and non-neural custom voice in 2024. After that, we'll no longer support them.
If your applications, tools, or products are using any of the standard voices and custom voices, you must migrate to the neural version. For more information, see Migrate to neural voices.
Sample code for text-to-speech is available on GitHub. These samples cover text-to-speech conversion in most popular programming languages:
When you use the text-to-speech feature, you're billed for each character that's converted to speech, including punctuation. Although the SSML document itself is not billable, optional elements that are used to adjust how the text is converted to speech, like phonemes and pitch, are counted as billable characters. Here's a list of what's billable:
- Text passed to the text-to-speech feature in the SSML body of the request
- All markup within the text field of the request body in the SSML format, except for
- Letters, punctuation, spaces, tabs, markup, and all white-space characters
- Every code point defined in Unicode
For detailed information, see Speech service pricing.
Each Chinese character is counted as two characters for billing, including kanji used in Japanese, hanja used in Korean, or hanzi used in other languages.