spokestack-python
mxnet
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| spokestack-python | mxnet | |
|---|---|---|
| 7 | 4 | |
| 132 | 20,644 | |
| - | - | |
| 3.3 | 4.1 | |
| over 2 years ago | 6 months ago | |
| Python | C++ | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
spokestack-python
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We're making it super easy to use voice in Python, and we want your feedback!
Our AutoML service will let you [redacted because we're not ready to say it publicly yet], using your own voice. Combining [redacted] with existing open-source SDK libraries & tutorials for [Python](https://github.com/spokestack/spokestack-python) allows you to utilize cutting-edge personalized voice technology.
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Sunday Daily Thread: What's everyone working on this week?
I’ve been working on this project for a while now. I’m really interested to discover if other developers want to add voice to their python projects.
I’ll be working on integrating spokestack into home-assistant
- Spokestack: Python Library for Voice Applications
- Spokestack: Embedded Voice Library for Python
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I love home assistant and I work on TTS in my day job. Should I do an add-on or an integration?
Ok so that’s my main concern. It seems like for distribution an integration is the way to go. Library is this for better context.
- Python Embedded Voice Library
mxnet
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List of AI-Models
Click to Learn more...
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Introduction to deep learning hardware in the cloud
Build – Choose a machine learning framework (such as TensorFlow, PyTorch, Apache MXNet, etc.)
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just released my Clojure AI book
Clojure and Python also have bindings to the Apache MXNet library. Is there a reason why you didn't use them in some of your projects?
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Can Apple's M1 help you train models faster and cheaper than Nvidia's V100?
> But you still lose something, e.g. if you use half precision on V100 you get virtually double speed, if you do on a 1080 / 2080 you get... nothing because it's not supported.
That's not true. FP16 is supported and can be fast on 2080, although some frameworks fail to see the speed-up. I filed a bug report about this a year ago: https://github.com/apache/incubator-mxnet/issues/17665
What consumer GPUs lack is ECC and fast FP64.
What are some alternatives?
picovoice - On-device voice assistant platform powered by deep learning
Caffe - Caffe: a fast open framework for deep learning.
silero-models - Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Porcupine - On-device wake word detection powered by deep learning
Caffe2
mlpack - mlpack: a fast, header-only C++ machine learning library
Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
Theano - Theano was a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It is being continued as PyTensor: www.github.com/pymc-devs/pytensor