AI Voice Cloning Tutorial: Create Any AI Voice with Kits.AI

Kits AI
3 Nov 202303:18

TLDRThis tutorial outlines the process of creating a high-quality AI voice model using Kits.AI. To achieve this, one requires 10 minutes of clean, dry monophonic vocals, avoiding any background noise, harmonies, or effects like reverb and delay. The quality of the input data directly impacts the voice model's output. Kits.AI allows users to upload their data set and train their voice model, with the option to use the vocal separator tool to extract vocals from a master recording. The tutorial also covers how to clean up vocals with the tool, remove unwanted elements, and train the model with YouTube links. Once trained, users can convert audio with dry monophonic input data, experiment with conversion settings, and even use the text-to-speech feature for their AI voice model. The tutorial emphasizes the importance of quality input data for the best results and the ease of using Kits.AI to create and convert AI voices.

Takeaways

  • 🎙️ To train a high-quality voice model, you need 10 minutes of dry monophonic vocals without any backing tracks or time-based effects.
  • 🔊 The quality of the voice model is directly related to the quality of the input data; clean recordings from a high-quality microphone in a lossless format are ideal.
  • 🚫 Avoid background noise, hum, and lossy compression artifacts as they can negatively impact the voice model's quality.
  • 🎶 Do not include harmony or doubling in your data set as it may lead to misinterpretation and glitches in the voice model.
  • 🎵 Be cautious of reverb and delay, which can cause overlapping voices and affect the voice model's accuracy.
  • 📈 Include a variety of pitches, vowels, and articulations in your data set to ensure the voice model can accurately convert a wide range of sounds.
  • 🎧 Use original recordings of the target voice, such as studio acappellas, for the best training data.
  • 🔍 If studio acappellas are not available, use the Kits vocal separator tool to extract vocals from a master recording.
  • 🧹 Clean up your vocals by removing reverb, echo, and backing vocals using the vocal separator tool.
  • 📚 Compile at least 10 minutes of good training data before uploading to Kits for training.
  • 🚀 Once the model is trained, you can easily convert audio with dry monophonic input data for the best results.
  • 🎛️ Experiment with conversion settings like the dynamic slider, pre- and post-processing effects to achieve the desired sound.
  • 📝 Utilize the text-to-speech feature to have your voice model speak out phrases typed by you.

Q & A

  • What is the minimum duration of dry monophonic vocals required to train a high-quality voice model?

    -To train a high-quality voice model, you need 10 minutes of dry monophonic vocals.

  • What should be avoided in the vocals used for training a voice model?

    -You should avoid backing tracks, time-based effects like reverb and delay, harmonies, doubling, and stereo effects in the vocals used for training a voice model.

  • How does the quality of the original recordings affect the voice model?

    -The quality of the original recordings, such as being from a high-quality microphone and in a lossless file format, will be reflected in the quality of the voice model.

  • Why should background noise and hum be avoided in the data set?

    -Background noise and hum can impact the quality of the voice model, potentially leading to glitches and artifacts in the converted audio.

  • What can happen if the data set contains harmony or doubling?

    -The voice model may misinterpret these additional voices as part of the original, which can lead to glitches and artifacts in the converted audio.

  • What should the data set include to ensure a comprehensive voice model?

    -The data set should include as many pitches, vowels, and articulations as possible to provide good examples for every sound the voice model will convert.

  • What is a good source of training data for a voice model?

    -The best source of training data is original recordings of the target voice, such as studio acappellas.

  • How can the kits vocal separator tool be used?

    -The kits vocal separator tool can be used to extract vocals from a master recording by dropping a file or pasting a YouTube link, which will isolate the main vocal from the backing track.

  • What can the vocal separator tool do to clean up the isolated vocals?

    -The vocal separator tool can remove backing vocals and eliminate reverb and echo to clean up the isolated vocals.

  • How does one start training their voice model once they have compiled the training data?

    -After compiling the training data, you head back to kits, upload your files, and start training.

  • What type of input data is best for converting audio with the trained voice model?

    -The best results for converting audio will come from dry monophonic input data.

  • How can one experiment with conversion settings and test new models?

    -One can experiment with conversion settings and test new models by using demo audio, which allows for unlimited audio conversion without using up convert minutes.

  • What additional feature can be used to test the voice model?

    -The text to speech feature can be used to type out a phrase for the voice model to speak out loud, providing another way to test the model's performance.

Outlines

00:00

🎤 Preparing High-Quality Voice Model Data

To train a high-quality voice model, you need to provide 10 minutes of clean, dry monophonic vocals without any backing tracks, time-based effects like reverb and delay, or any harmonies and doubling. The data set should be recorded using a high-quality microphone in a lossless file format to ensure the best results. The model captures every detail from the data set and uses it to create realistic audio conversions. It's crucial to avoid background noise, hum, and lossy compression artifacts, as they can degrade the model's quality. The data set should also include a wide range of pitches, vowels, and articulations to cover all sounds the model will need to convert. Original recordings of the target voice, such as studio acappellas, are ideal, but if not available, the kits vocal separator tool can be used to extract vocals from a master recording. The tool can also clean up vocals by removing reverb, echo, and harmonies. Once 10 minutes of good training data is compiled, it can be uploaded to kits for training.

Mindmap

Keywords

💡AI Voice Cloning

AI Voice Cloning refers to the technology that allows the creation of a synthetic voice that closely resembles a specific individual's voice. In the context of the video, it is the process of training a voice model using a dataset of vocal recordings to replicate the voice's unique characteristics. The video emphasizes the importance of using high-quality, dry monophonic vocals for training to achieve a realistic conversion.

💡Dry Monophonic Vocals

Dry Monophonic Vocals are recordings of a single voice without any additional musical accompaniment or effects. The video script specifies that these vocals are necessary for training an AI voice model because they provide a clear and unadulterated sample of the voice. This helps the AI to learn the nuances of the voice without interference from other sounds.

💡Training Data

Training Data is the set of vocal recordings used to teach the AI system how to replicate a particular voice. The script mentions that 10 minutes of dry monophonic vocals are needed for a high-quality voice model. The quality of the training data directly impacts the quality of the voice model, making it crucial to use clean, high-fidelity recordings.

💡Lossless File Format

A Lossless File Format is a type of digital file storage that retains all the original quality of the recorded audio without any compression or data loss. The video emphasizes using such formats for training data to ensure the highest possible quality of the voice model, as lossy compression can introduce artifacts that degrade the model's performance.

💡Vocal Separator Tool

The Vocal Separator Tool is a feature within the Kits.AI platform that allows users to extract the main vocal track from a master recording. This tool is useful for isolating vocals when original recordings are not available, as it can remove background music and other non-vocal elements. The script illustrates its use by showing how one can drop a file or paste a YouTube link to separate vocals.

💡Reverb and Delay

Reverb and Delay are audio effects that can add depth and space to a recording by simulating the natural reflections of sound in a physical environment. However, the video script advises against using these effects in the training data because they can cause overlapping voices and lead to misinterpretation by the AI, resulting in glitches in the voice model.

💡Harmony and Doubling

Harmony and Doubling refer to the musical techniques where multiple voices or instruments sing or play the same or related notes simultaneously. The script cautions against including these in the training data because the AI voice model might mistake them for the original voice, which can cause artifacts and glitches during the conversion process.

💡Pitches, Vowels, and Articulations

Pitches, Vowels, and Articulations are the fundamental components of speech that give a voice its unique sound. The video script suggests including a wide range of these elements in the training data to ensure that the AI voice model can accurately replicate every sound the user wants to convert. This comprehensive coverage helps in creating a more realistic and versatile voice model.

💡Conversion String Slider

The Conversion String Slider is a feature within the Kits.AI platform that allows users to adjust the conversion process of the audio. By experimenting with this slider, users can fine-tune the output to achieve the desired sound quality. The script does not provide specific details on how the slider works but implies that it is part of the customization process for audio conversion.

💡Dynamic Slider

The Dynamic Slider is another adjustable feature in the Kits.AI platform that likely affects the dynamic range or other aspects of the audio conversion process. The video suggests using this slider, along with pre- and post-processing effects, to optimize the sound of the converted audio. It is part of the customization tools that enable users to achieve the best results from their voice model.

💡Text-to-Speech Feature

The Text-to-Speech Feature enables users to input text that the AI voice model will then speak aloud. This is a useful tool for testing the voice model's capabilities and ensuring that it can accurately reproduce the intended speech. The script mentions this feature as a way to quickly test new models or conversion settings without using up conversion minutes.

💡Convert Minutes

Convert Minutes refer to the allotted time or capacity for converting audio using the AI voice model. The video script indicates that users can convert a significant amount of audio without using up their convert minutes, suggesting a generous allowance for users to experiment with the voice model and conversion settings.

Highlights

To train a high-quality voice model, you need 10 minutes of dry monophonic vocals.

Avoid backing tracks, time-based effects like Reverb and delay, and harmonies or stereo effects.

Clean recordings from a high-quality microphone in a lossless file format will reflect in your voice model.

Background noise, hum, and lossy compression artifacts can impact the quality of your voice model.

Harmony or doubling in your data set may lead to glitches and artifacts in your voice model.

Reverb and Delay can cause overlapping voices, so ensure your data set is as dry as possible.

Include a variety of pitches, vowels, and articulations in your data set for a more realistic conversion.

If the model hasn't trained on a sound, it can lead to scratchiness and glitches.

Original recordings of your target voice, like studio acappellas, are the best source of training data.

Use the Kits vocal separator tool to extract vocals from a master recording if you don't have access to acappellas.

The vocal separator tool can remove backing vocals and clean up reverb and echo.

Once you have compiled 10 minutes of good training data, upload your files to Kits and start training.

For easier training, you can paste YouTube links into Kits, which will automatically isolate vocals and train your model.

Dry monophonic input data will yield the best results in voice conversion.

Experiment with conversion string, dynamic slider, pre- and post-processing effects to achieve the best sound.

Use demo audio to quickly test new models or conversion settings without using up your conversion minutes.

The text-to-speech feature allows you to type a phrase for your voice model to speak out loud.

AI voice conversion is a powerful tool for creators, offering unlimited voice possibilities.

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