LangHelper VS dsnote

Compare LangHelper vs dsnote and see what are their differences.

LangHelper

Striving to create a great Application with full functions of learning languages by ChatGPT, TTS, STT and other awesome AI models, supports talking, speaking assessment, memorizing words with contexts, Listening test, so on. (by NsLearning)

dsnote

Speech Note Linux app. Note taking, reading and translating with offline Speech to Text, Text to Speech and Machine translation. (by mkiol)
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LangHelper dsnote
1 1
309 345
- -
6.6 9.8
6 months ago 3 days ago
Rust C++
MIT License Mozilla Public 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.

LangHelper

Posts with mentions or reviews of LangHelper. We have used some of these posts to build our list of alternatives and similar projects.

dsnote

Posts with mentions or reviews of dsnote. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing LangHelper and dsnote you can also consider the following projects:

silero-models - Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple

react-native-spokestack - Spokestack: give your React Native app a voice interface!

kraft - Kraft helps to handle your daily quotes and invoices in your small business.

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)

STT - 🐸STT - The deep learning toolkit for Speech-to-Text. Training and deploying STT models has never been so easy.