Part 3: Sound Like Darth Vader, T-Pain and More With the Apps for iOS and Androidĭarth Vader: Voice Actor/Star Wars/Fortnite Skinĭarth Vader is the one of the most iconic villains in popular culture, and has been listed among the greatest villains and fictional characters ever. Part 2: 4 Cool Darth Vader Voice Changers for Desktop | 0 Tesla T4 Off | 00000000:00:04.Part 1: Darth Vader: Voice Actor/Star Wars/Fortnite Skin | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. Open a new notebook in Colab, turn on a GPU runtime, and check your GPU: The added benefit is that I don’t need to mess with anything on my local computer, such as installing a bunch of dependencies or dealing with any installation errors that pop up. Note that Tortoise is a slow model (hence the name) and since my local computer doesn’t have an NVIDIA GPU, I decided to run this section’s code in a notebook environment on Google Colab. Now we’re ready to use Tortoise! We’ll be running it in inference mode we won’t be training or fine-tuning. I used an online M4A to WAV Converter that allowed me to specify the sample rate. Once you have created these audio clips, convert them to. Since I have a Mac machine, I used Apple’s Voice Memos app to trim my audio file to create short clips (which are saved in ~/Library/Application\ Support/). If you have existing software on your computer that you prefer to use, feel free to use it to create these clips. Pick higher-quality clips without background noise, if possible. Each clip should be about 6 to 10 seconds long, and I recommend having 5 to 10 clips total (I used 8 clips). Using Tortoise (text-to-speech)īefore using Tortoise, we need some short clips from our downloaded audio file of the voice we want to clone. Now that we’ve shown how to use Whisper to speech-to-text, let’s move on to speech generation in the next section. It took about 1 minute on my CPU to perform inference on a 13-minute audio file. Import pytube and define a YouTube object: For this step, I used a Jupyter notebook. Once installed, we can import the module in Python and start using it. I installed it using conda: conda install pytube. To do so, I used pytube ( docs), which is a dependency-free library for downloading YouTube videos. In order to perform speech tasks, the first step is to download audio from a YouTube video so that we have something to work with. Its development prioritized realistic intonation and rhythm in speech as well as multi-voice capabilities. Tortoise is a text-to-speech program by James Betker, and was trained on a dataset consisting of audiobooks.Whisper is open source and you can find it on GitHub, read the accompanying paper, or check out the OpenAI blog post. Whisper is an automatic speech recognition system released by OpenAI last month, and was trained on 680,000 hours of data (about one-third of its audio data is non-English). First, I’ll demonstrate how to download audio from a YouTube video, and then we’ll use it for these speech tasks. This blog post shows you how to perform speech recognition using Whisper (i.e., producing a written transcript of an audio file) and speech generation using Tortoise (i.e., creating an audio file based on someone’s voice for arbitrary text).
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |