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How can I create high-quality Text-to-Speech (TTS) systems that convey emotions effectively?

Early TTS systems were primarily focused on creating neutral, mechanical-sounding speech.

Emotional TTS systems use a combination of rule-based approaches and machine learning techniques to generate emotionally expressive speech.

Google's WaveNet uses a generative model that learns to predict the next audio sample based on previous samples, enabling more natural sounding speech.

Amazon Polly offers a range of emotional styles for its TTS voices, including joyful, angry, and sorrowful.

Concatenative synthesis involves combining pre-recorded units of speech to generate new expressions in emotional TTS systems.

The University of Southern California's Institute for Creative Technologies has developed a TTS system called MACH that can generate speech with various emotional attributes.

Emotional TTS systems create speech with various emotional dimensions, such as happiness, sadness, anger, and fear.

Rule-based approaches in emotional TTS use manually crafted rules to model emotional speech characteristics.

Machine learning techniques in emotional TTS learn emotional patterns from data-driven models.

SeedTTS, developed by ByteDance, offers superior controllability over various speech attributes such as emotion and is capable of generating highly expressive and diverse speech.

Emotional TTS systems use speech synthesis with mixed emotions and propose a self-distillation method for speech factorization to enhance model robustness.

The Emotivoice TTS engine supports both English and Chinese with over 2000 different voices.

The Emotivoice engine offers emotional synthesis, allowing the creation of speech with a wide range of emotions, including happy, excited, sad, angry, and others.

Emotional TTS systems can generate highly expressive and diverse speech for speakers in the wild, such as those in real-world environments.

ChatGPT's AI Voice Emotions Text To Speech Editor optimizes emotions for text-to-speech outputs utilizing SSML for dynamic and expressive voice synthesis.

LOVO AI offers emotional text-to-speech TTS, enabling users to directly make changes in the TTS block editor or use the Pronunciation Editor to automatically apply changes to all the TTS blocks.

Recent studies have measured increased inference time when comparing emotional speech to neutral speech in other emotional TTS implementations.

Typecast AI Voice Generator with Emotional Text to Speech enables users to include results for emotional text-to-speech, making text-to-speech with emotions using the typecast AI platform.

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