Repository navigation
language-identification
- Website
- Wikipedia
A collection of sample apps to demonstrate how to use Google's ML Kit APIs on Android and iOS
A Repository for Single- and Multi-modal Speaker Verification, Speaker Recognition and Speaker Diarization
The most accurate natural language detection library for Python, suitable for short text and mixed-language text
The most accurate natural language detection library for Go, suitable for short text and mixed-language text
The most accurate natural language detection library for Rust, suitable for short text and mixed-language text
The most accurate natural language detection library for Java and the JVM, suitable for long and short text alike
Cross-platform speech toolset, used from the command-line or as a Node.js library. Includes a variety of engines for speech synthesis, speech recognition, forced alignment, speech translation, voice isolation, language detection and more.
Simple embedding based text classifier inspired by fastText, implemented in tensorflow
Textpipe: clean and extract metadata from text
⚡️ 80x faster Fasttext language detection out of the box | Split text by language
Vietnamese NLP Toolkit for Node
Simple multilingual lemmatizer for Python, especially useful for speed and efficiency
💬 Language Identification with Support for More Than 2000 Labels -- EMNLP 2023
Implementation of the paper "Spoken Language Recognition using X-vectors" in Pytorch
Code for the paper Language Identification Using Deep Convolutional Recurrent Neural Networks
A TensorFlow-based spoken language identification
Fast and accurate natural language detection. Detector written in Javascript. Nito-ELD, ELD.
✨ Split text by languages (e.g. 你喜欢看アニメ吗 -> 你喜欢看 | アニメ | 吗) for NLP tasks (e.g. parse, TTS). Powered by fasttext and budoux
This code provides word level language identification tool for identifying language for individual words in Code-Mixed text. e.g. The text that includes words from two languages such as Hindi written in roman script, mixed with English.
End to End Dialect Identification using Convolutional Neural Network