TensorFlow_Lite_Classification_RPi_zero
TensorFlow Lite on a bare Raspberry Pi Zero (by Qengineering)
wav2letter
Facebook AI Research's Automatic Speech Recognition Toolkit (by flashlight)
| TensorFlow_Lite_Classification_RPi_zero | wav2letter | |
|---|---|---|
| 1 | 3 | |
| 8 | 6,339 | |
| - | 0.2% | |
| 10.0 | 4.6 | |
| over 1 year ago | 16 days ago | |
| C++ | C++ | |
| BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
TensorFlow_Lite_Classification_RPi_zero
Posts with mentions or reviews of TensorFlow_Lite_Classification_RPi_zero.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-24.
wav2letter
Posts with mentions or reviews of wav2letter.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-07-06.
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How to convert Speech-to-Text with Python?
Flashlight is a fast, flexible machine learning library written entirely in C++ from the Facebook AI Research Speech team and the creators of Torch and Deep Speech. Flashlight's ASR application (formerly the wav2letter project) provides training and inference capabilities for end-to-end speech recognition systems. This engine is really performant but you will need to compile all the C++ libraries before using it with Python.
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Open-source massively multilingual speech recognizer
Twitter was giving me a 500, so the goods are at https://github.com/flashlight/wav2letter/tree/main/recipes/mling_pl courtesy of the wayback machine
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Top Transcription APIs and Open Source Libraries in 2022
Wav2Letter, Facebook AI Research’s Automatic Speech Recognition (ASR)toolkit, is designed for research and developers to use for speech transcription.
What are some alternatives?
When comparing TensorFlow_Lite_Classification_RPi_zero and wav2letter you can also consider the following projects:
Maple-Syrup-Pi-Camera - Low power smart camera (3D printed) based on the Raspberry Pi Zero W and Google Coral EdgeTPU
STT - 🐸STT - The deep learning toolkit for Speech-to-Text. Training and deploying STT models has never been so easy.
DeepSpeech - DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
CIDLib - The CIDLib general purpose C++ development environment
openpose - OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
serving - A flexible, high-performance serving system for machine learning models