code-switch
ASR_Code_Switch
ASR Code-Switching Benchmark
A curated benchmark of 1,200 code-switching utterances (300 per language pair)
for evaluating commercial ASR systems on multilingual speech with intra-sentential
language switching.
Paper
Benchmarking Commercial ASR Systems on Code-Switching Speech: Arabic, Persian, and German
arXiv link
Language pairs
Split
Language pair
Samples
Scripts
egyptian_arabic_english
Egyptian Arabic–English
300
Arabic + Latin… See the full description on the dataset page: https://huggingface.co/datasets/Perle-ai/ASR_Code_Switch.code-switching-tokenizer-robustness
Code-Switching Dataset for Tokenizer Robustness Analysis
Dataset Description
This dataset is designed for tokenizer robustness testing in multilingual and code-switching contexts. It contains identical content expressed across 16 different language variants, including pure English and 15 English-X code-switching pairs, allowing researchers to isolate tokenization effects from semantic differences when evaluating language models.
Purpose
Tokenizer Comparison:… See the full description on the dataset page: https://huggingface.co/datasets/Malikeh1375/code-switching-tokenizer-robustness.saudi-english-code-switching-datasetko_commongen_v2_code_switching
🇰🇷🇺🇸🇯🇵🇨🇳🇪🇸 KoCommonGEN v2 Code-switching
This KoCommonGEN v2 Code-switching dataset consists of 99 samples for numerical commonsense reasoning, which were created relying on machine translation.
The dataset can be found on Hugging Face at: nlpai-lab/ko_commongen_v2_code_switching
This dataset contains code-switching data for the following languages:
Korean (korean)
English (english)
Japanese (japan)
Chinese (china)
Spanish (espanol)
(The code-switching data relies on… See the full description on the dataset page: https://huggingface.co/datasets/nlpai-lab/ko_commongen_v2_code_switching.Sinhala-English-Code-Mixed-Code-Switched-Dataset
Sinhala-English-Code-Mixed-Code-Switched-Dataset
This dataset contains 10,000 comments that have been annotated at the sentence level for sentiment analysis, humor detection, hate speech detection, aspect identification, and language identification.
The following is the tag scheme.
Sentiment - Positive, Negative, Neutral, Conflict
Humor - Humorous, Non humorous
Hate Speech - Hate-Inducing, Abusive, Not offensive
Aspect - Network, Billing or Price, Package, Customer Service, Data… See the full description on the dataset page: https://huggingface.co/datasets/NLPC-UOM/Sinhala-English-Code-Mixed-Code-Switched-Dataset.arazn_codeSwitched_mp3_full_notLower_notMultiDots_4_Turbo_new