ClariNet is a revolutionary text-to-speech architecture that uses an end-to-end approach. It is unlike previous TTS systems as it is fully convolutional and can be trained from scratch. ClariNet uses the WaveNet module which is conditioned on hidden states instead of the traditional mel-spectogram model used in other TTS systems. This new breakthrough in TTS systems is an exciting development for the future of TTS technology.
What is ClariNet?
ClariNet is an advanced text-to-speech (TTS) arch
Deep Voice 3: A Revolutionary Text-to-Speech System
If you're looking for an advanced text-to-speech system that offers high-quality audio output, then Deep Voice 3 (DV3) may be just what you're looking for. DV3 is an attention-based neural text-to-speech system that has quickly gained popularity among researchers and speech technology enthusiasts alike. The DV3 architecture boasts three main components – the encoder, decoder, and converter – each of which plays a critical role in delivering hi
Are you tired of robotic-sounding text-to-speech models? Look no further than FastPitch - a state-of-the-art, fully-parallel model based on FastSpeech that produces natural-sounding speech by conditioning on fundamental frequency contours.
What is FastPitch?
FastPitch is a text-to-speech model that utilizes FastSpeech architecture and two feed-forward Transformer (FFTr) stacks to produce high-quality, natural-sounding speech. Unlike other text-to-speech models, FastPitch is fully-parallel, wh
FastSpeech 2: Improving Text-to-Speech Technology
Text-to-speech (TTS) technology has greatly improved in recent years, but there is still a major challenge it faces called the one-to-many mapping problem. This refers to the issue where multiple speech variations correspond to the same input text, resulting in an inaccurate or robotic-sounding output. To address this problem, researchers have developed a new TTS model called FastSpeech 2, which aims to improve upon the original FastSpeech by di
FastSpeech 2s is an innovative text-to-speech model that generates speech directly from text during inference. This means that it skips mel-spectrogram generation and goes directly to waveform generation, making it a more efficient system. FastSpeech 2s has made two main design changes to the waveform decoder that have improved the model's capability.
Main Design Changes
The first major change that FastSpeech 2s has made is the use of adversarial training. Due to the difficulty of predicting
GAN-TTS is a type of software that uses artificial intelligence to generate realistic-sounding speech from a given text. It does this by using a generator, which produces the raw audio, and a group of discriminators, which evaluate how closely the speech matches the text that it is supposed to be speaking.
How Does GAN-TTS Work?
At its core, GAN-TTS is based on a type of neural network called a generative adversarial network (GAN). This architecture is composed of two main parts, the generato
Glow-TTS: The Cutting-Edge TTS System That Delivers Fast, Controllable, and High-Quality Speech Synthesis
If you are looking for a state-of-the-art text-to-speech system that delivers high-quality, natural-sounding speech, look no further than Glow-TTS.
Glow-TTS is a flow-based generative model for parallel TTS that is designed to produce speech that sounds more lifelike and natural than ever before. This innovative system is able to generate speech without the need for any external alignment
Overview of ParaNet: A text-to-speech model
ParaNet is a non-autoregressive attention-based architecture for text-to-speech conversion. It is a fully convolutional model that converts the input text into mel spectrograms, which is a visual representation of audio signals.
The ParaNet model is based on the autoregressive text-to-spectrogram model, Deep Voice 3. However, ParaNet differs from DV3 in its decoder design. While DV3 has multiple attention-based layers in its decoder, ParaNet has a si
What is Tacotron?
Tacotron is a generative text-to-speech model that was developed by researchers at Google. The model takes text as input and generates speech, producing a corresponding spectrogram that is then converted to waveforms. It uses a sequence-to-sequence (seq2seq) model with attention, which allows it to recognize and focus on important parts of the input text when generating speech.
How Does Tacotron Work?
The Tacotron model consists of three parts: an encoder, an attention-base
Tacotron 2 is a type of technology that allows for speech synthesis directly from written text. This means that a computer can take written words and turn them into spoken words by using a set of complex algorithms.
How It Works
Tacotron 2 consists of two main parts: a "recurrent sequence-to-sequence feature prediction network with attention" and a modified version of WaveNet.
The first component predicts a sequence of frames that represent mel spectrograms from an input sequence of characte
WaveTTS is a text-to-speech architecture that focuses on generating natural-sounding speech with high quality. It is based on the Tacotron model and uses two loss functions to measure the distortion between the natural and generated waveform, as well as the acoustic feature loss between the two.
Motivation
The motivation for creating WaveTTS is based on issues faced by the Tacotron 2 model. Here, the feature prediction network is trained independently of the WaveNet vocoder, which is used to