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Its speed and accuracy have led many to note that its generated voices sound near-indistinguishable from "real life", provided that sufficient computational specifications and resources (e.g., a powerful GPU and ample RAM) are available when running it locally and that a high-quality voice model is used. [2] [3] [4]
Audio deepfake technology, also referred to as voice cloning or deepfake audio, is an application of artificial intelligence designed to generate speech that convincingly mimics specific individuals, often synthesizing phrases or sentences they have never spoken.
A stack of dilated casual convolutional layers used in WaveNet [1]. In September 2016, DeepMind proposed WaveNet, a deep generative model of raw audio waveforms, demonstrating that deep learning-based models are capable of modeling raw waveforms and generating speech from acoustic features like spectrograms or mel-spectrograms.
Scrub, search, and bookmark audio to find, recall and assemble segments of audio files; Spectral analysis (FFT), speech synthesis (text-to-speech), and voice changer; Audio restoration tools including noise reduction and click pop removal [4] Supports sample rates from 6 to 96 kHz, stereo or mono, 8, 16, 24 or 32 bits; Remove vocals from music ...
Voice Finger – software that improves the Windows speech recognition system by adding several extensions to it. The software enables controlling the mouse and the keyboard by only using the voice. It is especially useful for aiding users to overcome disabilities or to heal from computer injuries.
Voice cloning is a case of the audio deepfake methods that uses artificial intelligence to generate a clone of a person's voice. Voice cloning involves deep learning algorithm that takes in voice recordings of an individual and can synthesize such a voice to the point where it can faithfully replicate a human voice with great accuracy of tone ...
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