![]() Ipd.Audio(().numpy(), rate=hparams.sampling_rate)Īfter hearing this voice you can understand, this TTS audio quality is near to human natural voice. Mel_outputs, mel_outputs_postnet, _, alignments = model.inference(sequence)Īudio = waveglow.infer(mel_outputs_postnet, sigma=0.666) Sequence = np.array(text_to_sequence(text, )) Text = "natural language processing is really awesome!" Now we are all set to generate realistic audio like human voice from text using deep learning model called Tecotro ![]() You can understand the power of this model. Those models are trained using LJ Speech Dataset which contains 24 hours of audio clips. Once downloaded paste them inside tacotron2 folder (git cloned folder) NVIDIA published their pre-trained model to use in your TTS project with Python freely. Pip install librosa -U Download Pre-trained model To solve the above error just uninstall librosa and joblib and install librosa again running below commands. You may face below errors while configuring Tecotron 2: AttributeError: 'CacheManager' object has no attribute 'cachedir'ĪttributeError: 'Memory' object has no attribute 'location' To configure jupyter notebook for your virtual environment execute below commands inside your environment: conda install jupyter To install Pytorch with CUDA run the below command conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch Setup Jupyter Notebook To work with Tecotron, you have to install PyTorch with CUDA. Note: If you want to install tensorflow for GPU you can follow this tutorial: Install TensorFlow GPU with Jupiter notebook for Windows Install Pytorch To install them run below commands: pip install tensorflow=1.15.0 You need to install some additional packages. Pip install -r requirements.txt Install Additional Packages To set up Tecotron 2 execute the following commands: git clone Inside the virtual environment execute the below commands one by one: Setup Tecotron 2 Note: Don’t change the python version else you may get the below TensorFlow error: Module 'tensorflow' has no attribute 'contrib' Here tts_python is the virtual environment name To create virtual environment run below command: conda create -n tts_python python=3.7 You can find the complete list of languages supported by gtts with their language code below: gtts languages listĪlso Read: Guide to Build Best LDA model using Gensim Python It supports several languages including Indian voices like Hindi, Tamil, Bengali (Bangla), Kannada and many more. GTTS (Google Text-to-Speech) is a Python library for interacting with Google Translate’s text-to-speech API. I found two of them very promising which can generate natural audio like real human. There are so many text to speech library in Python. ![]() Youtube videos: Nowadays using deep learning and AI TTS can generate audio like human voice which can use as voiceover for youtube videos.Siri: This product of Apple uses TTS in its background.Voice-enabled mobile Apps: A good example of this kind of app is Google Map drive navigation.E-Reader books: This kind of application can read a book or paper for you.Text to speech or TTS has several applications like: How DragGAN Works Application of Text to Speech
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