let me think, I eat hamburger for dinner.īelow is an example of Sara used in a chat bot scenario engaged in natural conversations with a human user. In addition, she is capable of reading emojis and making laughter, sighs, or special angry sounds and expressing emphasis such as “soooo good”, just like a human being would.Ĭheck out how those sound effects are like with the examples below. On her day 1 release, she is built in with three emotional styles: cheerful, sad, and angry. Sara, a new conversational voice in English (US), represents a young female adult that talks more casually and fits best for the chatbot scenarios. Sara: a new chatbot voice in English (US) Next, we introduce the latest updates in Azure Neural TTS conversational voices in different languages.
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In such cases, an AI voice that can support simultaneous speech and capture the casual speaking styles can make the speech-to-speech translation more vivid and engaging. Especially in the casual speech scenarios, the simultaneous speaking tones often provide the subtle nuances of the speech and help the audience build emotional connections with the speaker. During translation, it has been challenging, however, to keep the original speaker’s styles when his/her speech is translated to another language. With broad coverage of over 70 languages and variances, Azure Neural TTS has been used to provide speech output for various translations. Speech-to-speech translation is another typical scenario where a conversational AI voice can be used. In addition, expressing different emotions with different messages is also a high-demanded ask so the chat bot can better resonate human feelings. One challenge in making the AI-human chat more natural is for the bot to understand the chat language that usually contains special characters, modal particles like “hehe”, “haha”, “ouch”, emojis like, repeated letters like “soooo good” and provide instant responses in tones that are natural. With the emergence of virtual assistant and virtual reality technology, we’ve seen more customers using neural TTS in supporting chit-chats and daily conversations. Besides providing answers to the customer inquiries, the AI voice is also frequently used to give cheerful greetings and show empathy to customers. Now I’d like to know where you live.” In such scenarios, the AI voice is usually expected to sound comforting, friendly, warm, while being professional.
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After a customer gives their name, instead of a dry request like, “Now tell me your address,” TOBi might say, “Hey, that’s a great name. For example, Vodafone successfully created a natural-sounding customer service bot, TOBi, and used the AI and natural language processing capabilities in Azure to give TOBi a clear personality that could make conversations natural and fun, which drives better customer engagement.
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Many enterprises are using voice-enabled chatbots or IVR systems to provide more efficient customer services and transform their traditional customer care. We outline three typical scenarios for conversational voices or conversational styles below. In these scenarios, a more relaxed and casual speaking style is usually expected.
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More TTS voices are used to support human-machine conversations, or machine-facilitated interpersonal communications (e.g, human conversations supported with speech-to-speech translation). Today we are glad to announce a few updates on Neural TTS with a focus on the new voices that are optimized for casual conversation scenarios.Ĭonversational voices: scenarios and challenges and we have seen more customer requests to support natural conversations that are casual and less formal. Since its launch, Azure Neural TTS has been widely applied to all kinds of scenarios, from voice assistants to news reading and audiobook creation, etc. Neural Text to Speech (Neural TTS), a powerful speech synthesis capability of Cognitive Services on Azure, enables you to convert text to lifelike speech which is close to human-parity. This post is co-authored with Melinda Ma, Yueying Liu, Garfield He and Sheng Zhao