TensorFlowTTS
FairMOT
| TensorFlowTTS | FairMOT | |
|---|---|---|
| 6 | 2 | |
| 3,702 | 3,930 | |
| 0.9% | - | |
| 0.0 | 0.0 | |
| 5 months ago | 8 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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TensorFlowTTS
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Ask HN: On-Device Text to Speech
Hey HN, has anyone found a viable solution for doing this locally and offline on iOS? I'd like to offer a privacy-friendly text to speech feature to my App, and Apple's speech synthesis sounds awful compared to some newer models and TTS engines. The only thing I've found is an older TensorflowTTS example here: https://github.com/TensorSpeech/TensorFlowTTS/tree/master/examples/ios
Any pointers or tips appreciated.
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NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality
I had a lot of success using [FastSpeech2 + MB MelGAN via TensorFlowTTS](https://github.com/TensorSpeech/TensorFlowTTS). There are demos for [iOS](https://github.com/TensorSpeech/TensorFlowTTS/tree/master/ex...) and [Android](https://github.com/TensorSpeech/TensorFlowTTS/tree/master/ex...) which will allow you to run pretty convincing, modern TTS models with only a few hundred milliseconds of processing latency.
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TTS mobile help
I need an example of how I would go about it. I've combed through examples but it's just not clicking for me.
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A Working TTS feature has been found (No Google Services Required)
https://github.com/TensorSpeech/TensorFlowTTS was the project. It was pretty much a direct compile and run. I went through and added the required features to enable it as TTS service for Android. I also moved the Tensorflow portion into a separate thread from the TTS service directly, since Android restricts it's TTS service to a single thread, and the Tensorflow service uses five threads to run at a good speed. It's a much much heavier solution than a C/C++ compiled library, but it works out of the box and I will worry about optimizations later
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Free library for text-to-speech
You need to try, it implements most advanced algorithms and not as ad-hoc as nvidia https://github.com/TensorSpeech/TensorFlowTTS
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Reviving the 1973 Unix text to voice translator
For open source offline TTS with more or less recent algorithms you can check
https://github.com/TensorSpeech/TensorFlowTTS
FairMOT
- Does Multi Object Tracking work better (precision/recall) on videos than jury rigging a SOTA image object detection to work on videos?
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[D] Multi object tracking (MOT)
Looks like FairMOT (https://paperswithcode.com/paper/a-simple-baseline-for-multi-object-tracking) which has code available (https://github.com/ifzhang/FairMOT ).
What are some alternatives?
tortoise-tts - A multi-voice TTS system trained with an emphasis on quality
ByteTrack - [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
TTS - :robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
yolo_tracking - BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models
flowtron - Flowtron is an auto-regressive flow-based generative network for text to speech synthesis with control over speech variation and style transfer
FastMOT - High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
hifi-gan - HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
yolact - A simple, fully convolutional model for real-time instance segmentation.
Lip2Speech - A pipeline to read lips and generate speech for the read content, i.e Lip to Speech Synthesis.
darknet - YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )