UA-EdgeTranslator VS speechbrain

Compare UA-EdgeTranslator vs speechbrain and see what are their differences.

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UA-EdgeTranslator speechbrain
1 26
24 8,081
- 2.3%
7.9 9.7
14 days ago 7 days ago
C# Python
MIT License Apache License 2.0
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.

UA-EdgeTranslator

Posts with mentions or reviews of UA-EdgeTranslator. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-22.

speechbrain

Posts with mentions or reviews of speechbrain. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-22.

What are some alternatives?

When comparing UA-EdgeTranslator and speechbrain you can also consider the following projects:

espnet - End-to-End Speech Processing Toolkit

pyannote-audio - Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

Resemblyzer - A python package to analyze and compare voices with deep learning

ukrainian-onnx-model - An ONNX model for speech recognition of the Ukrainian language

SincNet - SincNet is a neural architecture for efficiently processing raw audio samples.

NeMo - A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)

speech-to-text-benchmark - speech to text benchmark framework

Kaldi Speech Recognition Toolkit - kaldi-asr/kaldi is the official location of the Kaldi project.

imgaug - Image augmentation for machine learning experiments.

denoiser - Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.

best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

ckip-transformers - CKIP Transformers

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