Our commitment to improving Azure AI Speech voices is unwavering, as we consistently work towards making them more expressive and engaging. Today, we are thrilled to announce a new and improved HD version of our neural text to speech service for selected voices. This new version further enhances the overall expressiveness, incorporating emotion detection based on the context of the input.

With innovative technology which uses acoustic and linguistic features to generate speech filled with rich, natural variations. It can adeptly detect emotional cues in the text and autonomously adjust the voice's tone and style. With this upgrade, you can expect a more human-like speech pattern characterized by improved intonation, rhythm, and emotion.

What is new?

Auto-regressive transformer language models have demonstrated remarkable efficacy in modelling tasks including text, vision and speech recently. We are now introducing new HD voices powered by language model-based structure. These new HD voices are designed to speak in the selected platform voice timber.  And it also provides some extra value:

\n
• Human-like speech generation: Our model not only interprets the input text accurately but also understands the underlying sentiment, automatically adjusting the speaking tone to match the emotion conveyed. This dynamic adjustment happens in real-time, without the need for manual editing, ensuring that each generated output is contextually appropriate and distinct.
\n
• Conversational: The new model excels at replicating natural speech patterns, including spontaneous pauses and emphasis. When given conversational text, it faithfully reproduces common phonemes like pauses and filler words. Instead of sounding like a reading of written text, the generated voice feels as if someone is conversing directly with you.
\n
• Prosody variations: Human voices naturally exhibit variation. Every sentence spoken by a human won’t be the same as any previously spoken ones. The new system enhances realism by introducing slight variations in each output, making the speech sound even more natural.
\n

Voice demos

HD voices come with a base model that understands the input text and predicts the speaking pattern accordingly. Check out samples below for a list of HD voices available, based on the ‘DragonHDLatestNeural’ model.

 Note:

\n
• The new voices are currently not listed in the Voice List API or documentation. However, you can access and use them by directly calling the SSML template. We will update the API and documentation with more details in the near future.
\n
• These HD voices are implemented based on the latest base model: DragonHDLatestNeural. The name before the colon, e.g, en-US-Andrew, is the voice persona name and its original locale.  The base model will be tracked by versions in future updates.
\n

Content Creation Demo

In a hectic work environment with many documents to read, converting them into podcasts for on-the-go listening can be beneficial. Here is a demo using Azure OpenAI GPT-4O and HD voices to create podcast content from PDF document. The same idea can be applied to any other documents like web pages, word documents etc.

The main steps of the demo are as follows:

\n
• Use Azure OpenAI GPT-4o to summarize a lengthy document.
\n
• Create a conversational podcast script.
\n
• Convert the script into audio featuring two hosts using Azure HD voices.
\n

Check out sample code on Github

Avatar Chat demo

HD voices can also be utilized with Azure Speech to text and TTS avatars, as well as GPT-4o in real-time full duplex conversations. This technology can enhance the interactive experience for customer service chatbots, among other applications.  We have published an avatar demo below:

\n
• It can support continuous conversations between the user and bot. 
\n
• It can support user interruption when the bot is speaking.
\n
• It can achieve end-to-end low latency through best practice using Azure OpenAI GPT-4o and speech services.
\n

How to use

You can start to use HD voices with the same speech synthesis SDK and REST APIs as non-HD voices. Follow the quick start to learn more about how to synthesize speech with SDK or learn to use the REST API here.

\n
• Voice Locale: The locale in the voice name indicates its original language and region.
\n
• Base Models: The current base model is DragonHDv1Neural. The latest version, DragonHDLatest, will be implemented once available. As more versions are introduced, you can specify the desired model (e.g., DragonHDv2Neural) according to the availability of each voice.
\n
• SSML Usage: To reference a voice in SSML, use the format voicename:basemodel.
\n
• Temperature Parameter: The temperature value is a float ranging from 0 to 1, influencing the randomness of the output.  You can also adjust the temperature parameter to control the variation of outputs. Here’s an example:\n
  \n
  • Lower Temperature: Results in less randomness, leading to more predictable outputs.
  \n
  • Higher Temperature: Increases randomness, allowing for more diverse outputs.
  \n
  • The default temperature is set at 1.0.
  \n
  • Less randomness yields more stable results, while more randomness offers variety but less consistency.
  \n
  \n
\n
• Availability: HD voices are currently in preview and will be accessible in three regions: East US, West Europe, and Southeast Asia.
\n
• Pricing: The cost for HD voices is $30 per 1 million characters.
\n

Example SSML:

<speak version='1.0' xmlns='http://www.w3.org/2001/10/synthesis' xmlns:mstts='https://www.w3.org/2001/mstts' xml:lang='en-US'>\n<voice name='en-US-Ava:DragonHDLatestNeural' parameters='temperature=0.8'>Here is a test</voice>\n</speak>

Note:

\n
• The new voices are currently not listed in the Voice List API or documentation. However, you can access and use them by directly calling the SSML template. We will update the API and documentation with more details in the near future.
\n
• These HD voices are implemented based on the latest base model: DragonHDLatestNeural. The name before the colon, e.g, en-US-Andrew, is the voice persona name and its original locale. The base model will be tracked by versions in future updates.
\n

Get started

In our ongoing quest to enhance multilingual capabilities in text-to-speech (TTS) technology, our goal is bringing the best voices to our product, our voices are designed to be incredibly adaptive, seamlessly switching languages based on the text input. They deliver natural-sounding speech with precise pronunciation and prosody, making them invaluable for applications such as language learning, travel guidance, and international business communication.

Microsoft offers over 500 neural voices covering more than 140 languages and locales. These TTS voices can quickly add read-aloud functionality for a more accessible app design or give a voice to chatbots, providing a richer conversational experience for users. Additionally, with the Custom Neural Voice capability, businesses can easily create a unique brand voice.

With these advancements, we continue to push the boundaries of what is possible in TTS technology, ensuring that our users have access to the most versatile and high-quality voices available.

For more information

\n
• Try our demo to listen to existing neural voices
\n
• Add Text-to-Speech to your apps today
\n
• Apply for access to Custom Neural Voice
\n
• Join Discord to collaborate and share feedback
\n

Our commitment to improving Azure AI Speech voices is unwavering, as we consistently work towards making them more expressive and engaging. Today, we are thrilled to announce a new and improved HD version of our neural text to speech service for selected voices. This new version further enhances the overall expressiveness, incorporating emotion detection based on the context of the input.

With innovative technology which uses acoustic and linguistic features to generate speech filled with rich, natural variations. It can adeptly detect emotional cues in the text and autonomously adjust the voice's tone and style. With this upgrade, you can expect a more human-like speech pattern characterized by improved intonation, rhythm, and emotion.

What is new?

Auto-regressive transformer language models have demonstrated remarkable efficacy in modelling tasks including text, vision and speech recently. We are now introducing new HD voices powered by language model-based structure. These new HD voices are designed to speak in the selected platform voice timber.  And it also provides some extra value:

\n
• Human-like speech generation: Our model not only interprets the input text accurately but also understands the underlying sentiment, automatically adjusting the speaking tone to match the emotion conveyed. This dynamic adjustment happens in real-time, without the need for manual editing, ensuring that each generated output is contextually appropriate and distinct.
\n
• Conversational: The new model excels at replicating natural speech patterns, including spontaneous pauses and emphasis. When given conversational text, it faithfully reproduces common phonemes like pauses and filler words. Instead of sounding like a reading of written text, the generated voice feels as if someone is conversing directly with you.
\n
• Prosody variations: Human voices naturally exhibit variation. Every sentence spoken by a human won’t be the same as any previously spoken ones. The new system enhances realism by introducing slight variations in each output, making the speech sound even more natural.
\n

Voice demos

HD voices come with a base model that understands the input text and predicts the speaking pattern accordingly. Check out samples below for a list of HD voices available, based on the ‘DragonHDLatestNeural’ model.

 Note:

\n
• The new voices are currently not listed in the Voice List API or documentation. However, you can access and use them by directly calling the SSML template. We will update the API and documentation with more details in the near future.
\n
• These HD voices are implemented based on the latest base model: DragonHDLatestNeural. The name before the colon, e.g, en-US-Andrew, is the voice persona name and its original locale.  The base model will be tracked by versions in future updates.
\n

Content Creation Demo

In a hectic work environment with many documents to read, converting them into podcasts for on-the-go listening can be beneficial. Here is a demo using Azure OpenAI GPT-4O and HD voices to create podcast content from PDF document. The same idea can be applied to any other documents like web pages, word documents etc.

The main steps of the demo are as follows:

\n
• Use Azure OpenAI GPT-4o to summarize a lengthy document.
\n
• Create a conversational podcast script.
\n
• Convert the script into audio featuring two hosts using Azure HD voices.
\n

Check out sample code on Github

Avatar Chat demo

HD voices can also be utilized with Azure Speech to text and TTS avatars, as well as GPT-4o in real-time full duplex conversations. This technology can enhance the interactive experience for customer service chatbots, among other applications.  We have published an avatar demo below:

\n
• It can support continuous conversations between the user and bot. 
\n
• It can support user interruption when the bot is speaking.
\n
• It can achieve end-to-end low latency through best practice using Azure OpenAI GPT-4o and speech services.
\n

Check out sample code on Github

How to use

You can start to use HD voices with the same speech synthesis SDK and REST APIs as non-HD voices. Follow the quick start to learn more about how to synthesize speech with SDK or learn to use the REST API here.

\n
• Voice Locale: The locale in the voice name indicates its original language and region.
\n
• Base Models: The current base model is DragonHDv1Neural. The latest version, DragonHDLatest, will be implemented once available. As more versions are introduced, you can specify the desired model (e.g., DragonHDv2Neural) according to the availability of each voice.
\n
• SSML Usage: To reference a voice in SSML, use the format voicename:basemodel.
\n
• Temperature Parameter: The temperature value is a float ranging from 0 to 1, influencing the randomness of the output.  You can also adjust the temperature parameter to control the variation of outputs. Here’s an example:\n
  \n
  • Lower Temperature: Results in less randomness, leading to more predictable outputs.
  \n
  • Higher Temperature: Increases randomness, allowing for more diverse outputs.
  \n
  • The default temperature is set at 1.0.
  \n
  • Less randomness yields more stable results, while more randomness offers variety but less consistency.
  \n
  \n
\n
• Availability: HD voices are currently in preview and will be accessible in three regions: East US, West Europe, and Southeast Asia.
\n
• Pricing: The cost for HD voices is $30 per 1 million characters.
\n

Example SSML:

Note:

\n
• The new voices are currently not listed in the Voice List API or documentation. However, you can access and use them by directly calling the SSML template. We will update the API and documentation with more details in the near future.
\n
• These HD voices are implemented based on the latest base model: DragonHDLatestNeural. The name before the colon, e.g, en-US-Andrew, is the voice persona name and its original locale. The base model will be tracked by versions in future updates.
\n

Get started

In our ongoing quest to enhance multilingual capabilities in text-to-speech (TTS) technology, our goal is bringing the best voices to our product, our voices are designed to be incredibly adaptive, seamlessly switching languages based on the text input. They deliver natural-sounding speech with precise pronunciation and prosody, making them invaluable for applications such as language learning, travel guidance, and international business communication.

Microsoft offers over 500 neural voices covering more than 140 languages and locales. These TTS voices can quickly add read-aloud functionality for a more accessible app design or give a voice to chatbots, providing a richer conversational experience for users. Additionally, with the Custom Neural Voice capability, businesses can easily create a unique brand voice.

With these advancements, we continue to push the boundaries of what is possible in TTS technology, ensuring that our users have access to the most versatile and high-quality voices available.

For more information

\n
• Try our demo to listen to existing neural voices
\n
• Add Text-to-Speech to your apps today
\n
• Apply for access to Custom Neural Voice
\n
• Join Discord to collaborate and share feedback
\n