heliport 0.7.0

Fast and accurate language identifier

heliport

A language identification tool which aims for both speed and accuracy. Mostly an efficient HeLI-OTS port to Rust, achieving 25x speedups while maintaining same accuracy levels.

Installation

From PyPi

Install it in your environment

pip install heliport

then download the binarized model

heliport download

From source

Install the requirements:

• Python
• PIP
• Rust
• OpenSSL

Clone the repo, build the package and binarize the model

git clone https://github.com/ZJaume/heliport
cd heliport
pip install .
heliport binarize

Usage

CLI

Just run the heliport identify command that reads lines from stdin

cat sentences.txt | heliport identify

eng_latn
cat_latn
rus_cyrl
...

Identify languages of input text

Usage: heliport identify [OPTIONS] [INPUT_FILE] [OUTPUT_FILE]

Arguments:
  [INPUT_FILE]   Input file, default: stdin
  [OUTPUT_FILE]  Output file, default: stdout

Options:
  -j, --threads <THREADS>                Number of parallel threads to use.
                                         0 means no multi-threading
                                         1 means running the identification in a separated thread
                                         >1 run multithreading [default: 0]
  -b, --batch-size <BATCH_SIZE>          Number of text segments to pre-load for parallel processing [default: 100000]
  -c, --ignore-confidence                Ignore confidence thresholds. Predictions under the thresholds will not be labeled as 'und'
  -s, --print-scores                     Print confidence score (higher is better) or raw score (higher is better) in case '-c' is provided
  -m, --model-dir <MODEL_DIR>            Model directory containing binarized model or plain text model. Default is Python module path or './LanguageModels' if relevant languages are requested
  -l, --relevant-langs <RELEVANT_LANGS>  Load only relevant languages. Specify a comma-separated list of language codes. Needs plain text model directory
  -h, --help                             Print help

Python package

>>> from heliport import Identifier
>>> i = Identifier()
>>> i.identify("L'aigua clara")
'cat_latn'

Remember to download or binarize the model first!

Rust crate

use std::path::PathBuf;
use heliport::identifier::Identifier;
use heliport::lang::Lang;

let identifier = Identifier::load(
    PathBuf::from("/path/to/model_dir",
    None,
    );
let lang, score = identifier.identify("L'aigua clara");
assert_eq!(lang, Lang::cat);

Differences with HeLI-OTS

Although heliport currently uses the same models as HeLI-OTS 2.0 and the identification algorithm is almost the same, there are a few differences (mainly during pre-processing) that may cause different results. However, in most case, these should not deacrease accuracy and should not happen frequently.

Note: Both tools have a pre-processing step for each identified text to remove all non-alphabetic characters.

The implementation differences that can change results are:

• HeLI during preprocessing removes urls and words beginning with @, while heliport does not.
• Since 1.5, during preprocessing, HeLI repeats every word that does not start with capital letter, This is probably to penalize proper nouns. However, in our tests, we have not find a significant improvement with this. Therefore,to avoid multiplying the cost of prediction by almost x2, this has not been implemented. In the future it might end up being implemented if there is need for it and can be implemented efficiently.
• Rust and Java sometimes have small differences on the smallest decimals in a float, so the stored n-gram probabilities are not exactly the same. But this is very unlikely to affect predicted labels.

Benchmarks

Speed benchmarks with 100k random sentences from OpenLID, all the tools running single-threaded:

tool	time (s)
CLD2	1.12
HeLI-OTS	60.37
lingua all high preloaded	56.29
lingua all low preloaded	23.34
fasttext openlid193	8.44
heliport	2.33