Introduction to Voice Cloning:
We often use voice cloning with other terms , like deepfake voice, speech synthesis, and synthetic voice, that have slightly different meanings. We use These terms often together, but they have slightly different meanings. Voice cloning is when someone uses a computer to make the speech of a real person, making a clone of their own unique voice. We use Artificial intelligence (AI) for this work. A text-to-speech (TTS) system is not the same as voice cloning. TTS systems can take a piece of written text and turn it into spoken language.
TTS systems are much more limited in what they can do than voice cloning technology, which is more of a one-on-one project. It is very important for any synthetically made media to have training data, which is what makes a voice come out. A TTS system uses that data to make a voice. There is a data set, and the voice we hear is the same one that we use/provide them in the set. Now, thanks to voice cloning AI technology, that is no longer the case. People have put methods have in place to get a deeper look at a target voice and figure out what it looks like and how it sounds. When ones apply characteristics to different waveforms of speech, someone can change the voice output of one voice to another.
How voice cloning is possible?
Deep learning, which is a type of machine learning that falls under the AI umbrella, has helped us make speech replications that are very close to the original. Only two things make this possible: We need a lot of powerful hardware with cloud computing abilities to process and render in a quick and efficient way .Large amounts of training data for the target voice, which models can use to make an accurate voice clone.
Having the right AI and development experience and tools is important, but it really comes down to the last thing. You’ll need a lot of recorded speech to help the voice model learn how to sound like the real thing. An embedding is a low-dimensional space where discrete variables that you can turn into high-dimensional vectors. This is where the computer stores voice information. We can use Machine learning models with a lot of data now because it is easier to use them. In order to keep things simple, we’ll stop there. If you want to learn more, feel free to do so.
Science Behind Voice Cloning with AI
Text-to-speech (TTS) interactions, also known as speech synthesis, have continually shown significant potential for machine learning and deep learning, two of AI’s basic technologies. When paired with speech recognition, the technique lays the groundwork for virtual assistants such as Siri and Alexa. On the other hand, chatbot development businesses are still attempting to eliminate the robotic intonation associated with voice-controlled assistants.
With voice cloning, deep neural networks are one step closer to delivering high-quality, engaging, personalized, and incredibly intuitive human-chatbot interactions.Speech Vector to TTS (SV2TTS) is a tool that uses only a few seconds of a sample voice to synthesize speech audio that is nearly identical. SV2TTS may be done for a fraction of the expense of typical training methods, for which we should provide many hours of professionally recorded speech.
a) The AI cloned the voices, but have not received considerable training or retraining.
c) Provide high-resolution audio output, and
c) During training, synthesize natural speech from unknown speakers.
In the model overview above, the SV2TTS system comprises of three individually trained components :
- Speaker Encoder Network
- Neural Vocoder
Baidu researchers developed Deep Voice, a text-to-speech (TTS) system. Deep Voice 1 was influenced by traditional text-to-speech pipelines in its first version. The structure remains the same, but all of the components is now replaced with neural networks, and the features have been simplified. It converts text to phonemes first, then employs an audio synthesis model to convert linguistic data into speech.
Deep Voice 3, the most latest iteration of this research, features a fully convolutional character-to-spectrogram architecture. Its architecture allows for totally parallel processing, which allows it to train quicker than recurrent networks. Its design is inspired by Transformers (Vaswani et al). Deep Voice 3 TTS was the first system to scale from a single model to thousands of speakers.
- Baidu’s AI system needs just a 3 second sample to clone your voice
- Researchers used speaker adaptation and speaker encoding to develop it
- Check out their audio samples and research paper below
Chinese internet search giant Baidu has developed an AI system that can clone an individual’s voice! An year in the making, the text to speech system, called Deep Voice, can generate synthetic human voices using deep neural networks.
According to the information shared by Baidu Research, they claim that it takes their trained model just three seconds to replicate and output a person’s voice.
Baidu’s research team created the AI system utilizing voice cloning techniques, which they believe will be useful in personalizing human-machine interfaces. They used a two-pronged method to develop their neural cloning technology:
• Speaker adaptation: It is based on a backpropagation-based multi-speaker generative model.
• Speaker encoding: It combines the model that generates speaker embedding from cloned audio with the multi-speaker generative model to accelerate cloning.
Speaker Adaptation and Speaker Encoding (which need minimal audio) both provide high-quality performance and can be employed in the Deep Voice model with speaker embeddings without sacrificing the source audio’s quality.
You can hear some audio samples provided by Baidu’s Research team (https://audiodemos.github.io/) that include both original and synthesized voices. They have also published an official research paper, which you can see here (https://arxiv.org/abs/1802.06006).
Respeecher is an online program that combines deep learning and artificial intelligence to make a person’s voice sound like that of a famous person in real time while they talk. This technology may be extremely beneficial to filmmakers, game developers, and businesses who wish to showcase their products. It works really well in this scenario and produces a high-quality outcome by incorporating human emotions into the speech.
How to use?
speech-to-speech technology to make your voice sound like someone else’s.
Usually, professional who work with real-time voice cloning software know how to keep their data private so it can’t be stolen and used for nefarious purposes. Use this voice cloning program to perform the following tasks:
- The client must obtain permission from the person whose voice will be utilized before cloning or dubbing it.
- The next step is to record the individual you wish to speak with in a high-quality voice recording.
- Record the same lines as the aim to acquire more accurate data from the source.
- Voice cloning software will employ AI to create models for voice cloning.
- This is the final phase in the process. All you have to do now is use the microphone to record your voice, and we’ll do real-time voice cloning and provide you with a high-quality cloned voice.
Thanks to technical advancements, artificial intelligence has created a number of breakthroughs, including real-time vocal cloning and the capacity to make one’s own voice seem like someone else’s. Its mission is to serve and contribute to the community in a variety of ways, including supporting disadvantaged individuals and increasing audience visibility. You can rapidly clone your voice or transform your text-to-speech into the voice of another person using some of the best voice cloning tools available. So, rather than wasting time, look into some real-time voice copying software that meets your needs.
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