tensorflow-speech-recognition
Speech recognition using TensorFlow deep learning framework
GraphCanon updated 3w · GitHub synced 3w · 26 views this month
Decision brief
tensorflow-speech-recognition is a repository offering speech-to-text functionality powered by sequence-to-sequence neural networks and the TensorFlow deep-learning framework in Python.
Good fit when
- When you need to integrate speech-to-text capabilities leveraging the advanced capabilities of TensorFlow for optimal accuracy
- To benefit from less trivial architectures such as 'densenet_layer.py' for more sophisticated tasks beyond basic classification
Avoid when
- If real-time performance is a priority, due to its computational demands from TensorFlow's deep-learning models
- When aiming to use a lightweight model for embedded systems with limited processing power, as it relies heavily on TensorFlow which can be resource-intensive
- Pricing:
- freemium - The repository itself is free and open-source under the 'Other' license, but users should consider potential costs associated with running TensorFlow on their infrastructure.
- Requirements:
- Min 4 GB RAM; Requires Python environment setup including TensorFlow
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (925d since push)
- As of 3w
- Provenance
- Not a fork · Personal account
- As of 3w
- Security (OSV)
- No criticals
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install tensorflow-speech-recognitionSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
This repository provides speech-to-text functionality utilizing sequence-to-sequence neural networks and the TensorFlow deep-learning framework.
Capability facts
- Languages
- python
Source: github.language · Jul 30, 2026
Categories
Tags
README
Getting started
Toy examples:
./number_classifier_tflearn.py
./speaker_classifier_tflearn.py
Some less trivial architectures:
./densenet_layer.py
Later:
./train.sh
./record.py
Update: Nervana demonstrated that it is possible for 'independents' to build speech recognizers that are state of the art.
For agents
This page has a .md twin and JSON over the API.