According to identify the difference between actual human

According to the father of Artificial Intelligence, John McCarthy, it is “The science and engineering of making intelligent machines, especially intelligent computer programs”. In other word we can say that Artificial Intelligence is a sense or logic which showed and learned by a machine, In Machine language it is called Machine Intelligence (MI)  but  in the field of computer science the AI is a study of “Intelligent Agents”.What is Artificial IntelligenceIn short word “Artificial Intelligence” is applied when a machine mimics perceptual function that human associate with other human mind such as “learning” “problem solving” and “reading”.What Is Artificial Intelligence in Shorts:Artificial intelligence was founded as an academic discipline in 1956  by John McCarthy for the Dartmouth Conferences who defined it is as “the science and engineering of making intelligent machines”. The term is catchy and has caught the public imagination ever since.              But now here is question about the Can you tell the difference between AI-generated computer speech and a real, live human being? Maybe you’ve always thought you could. Maybe you’re fond of Alexa and Siri but believe you would never confuse either of them with an actual woman.What is Google’s Artificial Intelligence (AI) Tacotron 2:Generating very natural sound and speech like a human being from text has been research goal for engineers for a decades, speech from text is know as the text-to-speech,(TTS). Now, In the filed of text to speech last few year their is lots of progress but many individual and other energetic person and they complete TTS system have greatly improved. past work such as Tacotron and WaveNet, we added more improvements to end up with our new system, Tacotron 2.                                After lot’s of hard work by Google engineers  make it possible to identify the difference between actual human voice and Artificial Intelligence voice and rectify it by 12 months hard work. They worked the last 12 months they have worked hard to significantly improve both the speed and quality of their model and today they announced the “Tacotron 2”.                     Upgraded version of tacotron, Tacotron is a sequence-to-sequence architecture for producing magnitude spectrograms from a sequence of characters i.e. it synthesizes speech directly from words. It uses a single neural network trained from data alone for production of the linguistic and acoustic features. Tacotron uses the Griffin-Lim algorithm for phase estimation. Griffin-Lim produces characteristic artifacts and lower audio fidelity than approaches like WaveNet. As in describe in paper “NATURAL TTS SYNTHESIS BY CONDITIONING WAVENET ON MEL SPECTROGRAM PREDICTIONS”. Flow Diagram Of Tacotron 2The system first creates a spectrogram of the text, a visual representation of how the speech should sound. That image is put through Google’s existing WaveNet algorithm, which uses the image and brings AI closer than ever to in-discernibly mimicking human speech. The algorithm can easily learn different voices and even generates artificial breaths. In a short details We use a sequence-to-sequence model optimized for TTS to map a sequence of letters to a sequence of features that encode the audio. These features, an 80-dimensional audio spectrogram with frames computed every 12.5 milliseconds, capture not only pronunciation of words, but also various subtleties of human speech, including volume, speed and intonation.Tacotron 2 is an ene-to-end neural text-to-speech system that combined a sequence-to-sequence recurrent network with attention to predicts mel synthesizes speech with Tacotron-level prosody and WaveNet-level audio quality. Tacotron 2  sound quality close to that of natural human speech.Key feature of Tacotron 2:Have a look on the key feature of Tacotron 2-These features are converted to a waveform of 24 kHz using a WaveNet-like architecture.Tacotron model achieves a mean opinion score (MOS) of 4.53 comparable to a MOS of 4.58 for professionally recorded speech. Tacotron uses the Griffin-Lim algorithm for phase estimation.It can correctly pronounce identically-spelled words like ‘read’ (to read) and ‘read’ (has read).It can breath like a human but its breath is artificial.Here is example of a few Audio samples from “Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions” could you really tell the difference, or did you just have to guess?

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