Microsoft’s Neural TTS can be used to make interactions with chatbots and virtual assistants more natural and engaging
Microsoft India has announced the addition of English (India) and Hindi to its Neural Text to Speech (Neural TTS) service language set. The two Indian languages are among the 15 new dialects added to the service enabled with state-of-the-art AI audio quality.
Neural TTS is a part of the Azure Cognitive Services and converts text to lifelike speech for a more natural interface. The service also provides customizable voices, fine-tuned auto control, and flexible deployment from cloud to edge.
With natural-sounding speech that matches the stress patterns and intonation of human voices, Neural TTS significantly reduces listening fatigue when users are interacting with AI systems. This makes the service ideal for developing interfaces to communicate with customers.
Microsoft’s Neural TTS can be used to make interactions with chatbots and virtual assistants more natural and engaging. It is also being used to convert digital texts such as e-books into audiobooks and being deployed for in-car navigation systems. The service enables human-like natural and clear articulation and uses deep neural networks to overcome the limits of traditional text-to-speech systems in matching the patterns of stress and pitch in spoken language. Neural TTS offers these benefits while maintaining comprehensive privacy and enterprise-grade security through data encryption.
The other new languages introduced are Arabic (Egypt and Saudi Arabia), Danish, Finnish, Catalan, Polish, Dutch, Portuguese, Russian, Thai, Swedish, and Chinese (Cantonese Traditional and Taiwanese Mandarin). Overall, Microsoft TTS supports 110 voices and over 45 languages and variants.
Organizations across sectors like telecom, media, and entertainment, retail, manufacturing, and product/ service development are using Neural TTS. Udaan, India’s largest online business-to-business (B2B) marketplace, is using Text to Speech in Azure to develop conversational interfaces for their voice assistants.
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