What is text-to-speech?
Text-to-speech from Azure Speech Services is a service that enables your applications, tools, or devices to convert text into natural human-like synthesized speech. Choose from standard and neural voices, or create your own custom voice unique to your product or brand. 75+ standard voices are available in more than 45 languages and locales, and 5 neural voices are available in 4 languages and locales. For a full list, see supported languages.
Text-to-speech technology allows content creators to interact with their users in different ways. Text-to-speech can improve accessibility by providing users with an option to interact with content audibly. Whether the user has a visual impairment, a learning disability, or requires navigation information while driving, text-to-speech can improve an existing experience. Text-to-speech is also a valuable add-on for voice bots and virtual assistants.
By leveraging Speech Synthesis Markup Language (SSML), an XML-based markup language, developers using the text-to-speech service can specify how input text is converted into synthesized speech. With SSML, you can adjust pitch, pronunciation, speaking rate, volume, and more. For more information, see SSML.
Standard voices are created using Statistical Parametric Synthesis and/or Concatenation Synthesis techniques. These voices are highly intelligible and sound natural. You can easily enable your applications to speak in more than 45 languages, with a wide range of voice options. These voices provide high pronunciation accuracy, including support for abbreviations, acronym expansions, date/time interpretations, polyphones, and more. Use standard voice to improve accessibility for your applications and services by allowing users to interact with your content audibly.
Neural voices use deep neural networks to overcome the limits of traditional text-to-speech systems in matching the patterns of stress and intonation in spoken language, and in synthesizing the units of speech into a computer voice. Standard text-to-speech breaks down prosody into separate linguistic analysis and acoustic prediction steps that are governed by independent models, which can result in muffled voice synthesis. Our neural capability does prosody prediction and voice synthesis simultaneously, which results in a more fluid and natural-sounding voice.
Neural voices can be used to make interactions with chatbots and virtual assistants more natural and engaging, convert digital texts such as e-books into audiobooks and enhance in-car navigation systems. With the human-like natural prosody and clear articulation of words, neural voices significantly reduce listening fatigue when you interact with AI systems.
Neural voices support different styles, such as neutral and cheerful. For example, the Jessa (en-US) voice can speak cheerfully, which is optimized for warm, happy conversation. You can adjust the voice output, like tone, pitch, and speed using Speech Synthesis Markup Language. For a full list of available voices, see supported languages.
To learn more about the benefits of neural voices, see Microsoft’s new neural text-to-speech service helps machines speak like people.
Voice customization lets you create a recognizable, one-of-a-kind voice for your brand. To create your custom voice font, you make a studio recording and upload the associated scripts as the training data. The service then creates a unique voice model tuned to your recording. You can use this custom voice font to synthesize speech. For more information, see custom voices.
Speech Synthesis Markup Language (SSML)
Speech Synthesis Markup Language (SSML) is an XML-based markup language that lets developers specify how input text is converted into synthesized speech using the text-to-speech service. Compared to plain text, SSML allows developers to fine-tune the pitch, pronunciation, speaking rate, volume, and more of the text-to-speech output. Normal punctuation, such as pausing after a period, or using the correct intonation when a sentence ends with a question mark are automatically handled.
All text inputs sent to the text-to-speech service must be structured as SSML. For more information, see Speech Synthesis Markup Language.
When using the text-to-speech service, you are billed for each character that is converted to speech, including punctuation. While 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 service 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 Pricing.
Each Chinese, Japanese, and Korean language character is counted as two characters for billing.
This table lists the core features for text-to-speech:
|Convert text to speech.||Yes||Yes|
|Upload datasets for voice adaptation.||No||Yes*|
|Create and manage voice font models.||No||Yes*|
|Create and manage voice font deployments.||No||Yes*|
|Create and manage voice font tests.||No||Yes*|
* These services are available using the cris.ai endpoint. See Swagger reference. These custom voice training and management APIs implement throttling that limits requests to 25 per 5 seconds, while the speech synthesis API itself implements throttling that allows 200 requests per second as the highest. When throttling occurs, you'll be notified via message headers.
Get started with text to speech
We offer quickstarts designed to have you running code in less than 10 minutes. This table includes a list of text-to-speech quickstarts organized by language.
|Quickstart (SDK)||Platform||API reference|
|C#, .NET Core||Windows||Browse|
|C#, .NET Framework||Windows||Browse|
|C#, Unity||Windows, Android||Browse|
|Quickstart (REST)||Platform||API reference|
|C#, .NET Core||Windows, macOS, Linux||Browse|
|Node.js||Window, macOS, Linux||Browse|
|Python||Window, macOS, Linux||Browse|
Sample code for text-to-speech is available on GitHub. These samples cover text-to-speech conversion in most popular programming languages.
- Speech SDK
- Speech Devices SDK
- REST API: Speech-to-text
- REST API: Text-to-speech
- REST API: Batch transcription and customization