**Google AI’s Text-to-Speech Model Breaks New Ground in Expressiveness and Naturalness**.
Researchers at Google AI have developed a new text-to-speech (TTS) model that sets a new benchmark for expressiveness and naturalness. The model, called Tacotron 2, generates speech that is indistinguishable from human speech to the average listener..
Tacotron 2 is based on a deep neural network that learns to map text to speech. The model is trained on a large dataset of human speech, and it learns to capture the subtle nuances of human speech, such as intonation, stress, and timing..
Tacotron 2 is a significant improvement over previous TTS models. Previous models were often robotic and unnatural-sounding, but Tacotron 2 generates speech that is highly expressive and natural..
The researchers evaluated Tacotron 2 on a set of human-recorded speech samples. They found that the average listener could not distinguish between speech generated by Tacotron 2 and speech recorded from a human speaker..
Tacotron 2 has a wide range of potential applications. It can be used to create audiobooks, podcasts, and other spoken-word content. It can also be used to develop new voice-based interfaces for devices such as smartphones and smart speakers..
Tacotron 2 is a major breakthrough in the field of speech synthesis. It is the first TTS model to generate speech that is indistinguishable from human speech to the average listener. This breakthrough has the potential to revolutionize the way we interact with computers and other devices..
**How Tacotron 2 Works**.
Tacotron 2 is a deep neural network that learns to map text to speech. The model is composed of two main components: an encoder and a decoder..
The encoder converts the input text into a sequence of numbers. The decoder then uses the sequence of numbers to generate the speech waveform..
The encoder is a convolutional neural network (CNN). The CNN learns to identify the phonemes (the basic units of speech) in the input text. The decoder is a recurrent neural network (RNN). The RNN learns to generate the speech waveform by predicting the next sample in the sequence..
Tacotron 2 is trained on a large dataset of human speech. The dataset contains over 100 hours of speech from professional voice actors. The model is trained using a technique called maximum likelihood estimation..
Maximum likelihood estimation is a method of training a model by minimizing the difference between the model’s output and the desired output. In the case of Tacotron 2, the desired output is the speech waveform of the input text..
**Applications of Tacotron 2**.
Tacotron 2 has a wide range of potential applications, including:.
* **Audiobooks:** Tacotron 2 can be used to create audiobooks that are highly expressive and natural-sounding. This will make it easier for people to enjoy audiobooks, especially those with visual impairments..
* **Podcasts:** Tacotron 2 can be used to create podcasts that are engaging and informative. The model’s ability to generate natural-sounding speech will make it easier for listeners to stay focused on the content of the podcast..
* **Voice-based interfaces:** Tacotron 2 can be used to develop new voice-based interfaces for devices such as smartphones and smart speakers. This will make it easier for people to interact with their devices and get the information they need..
Tacotron 2 is a major breakthrough in the field of speech synthesis. It is the first TTS model to generate speech that is indistinguishable from human speech to the average listener. This breakthrough has the potential to revolutionize the way we interact with computers and other devices..
