SOTAVerified

Language Identification

Language identification is the task of determining the language of a text.

Papers

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Showing 226–250 of 794 papers

TitleStatusHype
Discriminating Similar Languages with Token-Based Backoff—0
Accurate Pinyin-English Codeswitched Language Identification—0
Cross-lingual Inductive Transfer to Detect Offensive Language—0
Distinguishing Literal and Non-Literal Usage of German Particle Verbs—0
Distributed Representations of Words and Documents for Discriminating Similar Languages—0
Distributional Interaction of Concreteness and Abstractness in Verb--Noun Subcategorisation—0
DKPro TC: A Java-based Framework for Supervised Learning Experiments on Textual Data—0
DLRG@DravidianLangTech-EACL2021: Transformer based approachfor Offensive Language Identification on Code-Mixed Tamil—0
Do Characters Abuse More Than Words?—0
Cross-domain Feature Selection for Language Identification—0
Automatic Detection of Sentence Fragments—0
An Exploratory Analysis of the Relation Between Offensive Language and Mental Health—0
Cross-corpus Native Language Identification via Statistical Embedding—0
Cross-Corpora Spoken Language Identification with Domain Diversification and Generalization—0
Duluth at SemEval-2020 Task 12: Offensive Tweet Identification in English with Logistic Regression—0
Dyn-ASR: Compact, Multilingual Speech Recognition via Spoken Language and Accent Identification—0
Efficient Discrimination Between Closely Related Languages—0
Efficiently Identifying Low-Quality Language Subsets in Multilingual Datasets: A Case Study on a Large-Scale Multilingual Audio Dataset—0
Emad at SemEval-2019 Task 6: Offensive Language Identification using Traditional Machine Learning and Deep Learning approaches—0
Automatic Detection of Intra-Word Code-Switching—0
Cross-Corpora Language Recognition: A Preliminary Investigation with Indian Languages—0
Automatic Detection of Code-switching Style from Acoustics—0
A Neural Model for Language Identification in Code-Switched Tweets—0
Enhancing Code-Switching ASR Leveraging Non-Peaky CTC Loss and Deep Language Posterior Injection—0
A Fast, Compact, Accurate Model for Language Identification of Codemixed Text—0
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All datasetsVOXLINGUA107GlotLID-CNordic Language IdentificationOpenSubtitlesUniversal DependenciesVoxForge

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1wav2vec 2.0 LV-60KError rate7.2—Unverified
2XLS-RError rate5.7—Unverified
#ModelMetricClaimedVerifiedStatus
1GlotLIDMacro F10.98—Unverified
#ModelMetricClaimedVerifiedStatus
1FastTextAccuracy0.97—Unverified
#ModelMetricClaimedVerifiedStatus
1Apple bi-LSTMAccuracy91.37—Unverified
#ModelMetricClaimedVerifiedStatus
1Apple bi-LSTMAccuracy86.93—Unverified
#ModelMetricClaimedVerifiedStatus
1ConformerG-PAccuracy99.8—Unverified