datitran
Joined 9 years ago
Joined 9 years ago
At priceloop, we are working on a completely novel way of how businesses can run their pricing. Like really really novel. Not just another AI model for pricing. We strive to redefine this software category.
That's why we're looking for full-stack Scala software engineers to build our no-code pricing platform. The team is small but experienced. We also love open-source, in fact some of us are maintainers and contributors of some well-known projects such as outwatch, a functional and reactive web-frontend library for ScalaJS. Once we developed the core platform, we are also planing to open-source it. Our tech stack is Postgres, Docker, Kubernetes and we deploy on AWS.
More details here: https://priceloopai.notion.site/Working-at-Priceloop-ed8b442...
- Samples: https://as-ideas.github.io/TransformerTTS/
The best thing on our implementation though is that you can easily use the WaveRNN Vocoder to generate human-level synthesis. We also provide samples and a Colab notebook. Make sure to check it out and please star ⭐️ the repo and share it! We're already working on the Forward version of TransformerTTS and we'll release it soon as well.
- Samples: https://as-ideas.github.io/TransformerTTS/
- Github: https://github.com/as-ideas/TransformerTTS
- Colab notebook: https://colab.research.google.com/github/as-ideas/Transforme...
The model has several advantages:
* Robustness: No repeats and failed attention modes for complex sentences
* Speed: Generating a spectrogram takes about 0.04s on a RTX2080
* Controllability: You can control the speed of the speech synthesis
️* Efficiency: No usage of attention so memory size grows linearly with text size
We also provide a Colab notebook to try out our pre-trained model trained 100k steps on LJSpeech and also some Samples. Check it out!
* Github: https://github.com/as-ideas/ForwardTacotron
* Samples: https://as-ideas.github.io/ForwardTacotron/
* Colab notebook: https://colab.research.google.com/github/as-ideas/ForwardTac...
We built this library with the following goals in mind. Firstly, it offers a simple API for training and deployment of models (only a few lines of code). Secondly, it uses TensorFlow 2.0 with all its new features. Thirdly, it has modular classes: text preprocessing, modeling, evaluation and is easily extensible for new models and finally works well on large text data.
Headliner is our first NLP project that we open-sourced and we're happy about this. Please try out our library, star it on Github and spread the word! We'd love to get feedback.