Papers Language Identification
“Language Identification” 태그가 달린 논문 852편 · 필터 해제
Recursive Semantic Anchoring in ISO 639:2023: A Structural Extension to ISO/TC 37 Frameworks
ISO 639:2023 unifies the ISO language-code family and introduces contextual metadata, but it lacks a machine-native mechanism for handling dialectal drift and creole mixtures. We propose a formalisation of recursive sema…
Language IdentificationTalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge
This paper describes the language identification and multilingual speech recognition system developed at Tallinn University of Technology for the Interspeech 2025 ML-SUPERB 2.0 Challenge. A hybrid language identification…
Language Identificationspeech-recognitionSpeech RecognitionImproving Multilingual Speech Models on ML-SUPERB 2.0: Fine-tuning with Data Augmentation and LID-Aware CTC
Multilingual speech processing with self-supervised or supervised pre-trained Speech Foundation Models (SFM) has achieved strong performance on tasks like Language Identification (LID) and Automatic Speech Recognition (A…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Data AugmentationLanguage Identification+2CosyVoice 3: Towards In-the-wild Speech Generation via Scaling-up and Post-training
In our prior works, we introduced a scalable streaming speech synthesis model, CosyVoice 2, which integrates a large language model (LLM) and a chunk-aware flow matching (FM) model, and achieves low-latency bi-streaming …
Automatic Speech RecognitionEmotion RecognitionEvent DetectionLanguage Identification+5Token Masking Improves Transformer-Based Text Classification
While transformer-based models achieve strong performance on text classification, we explore whether masking input tokens can further enhance their effectiveness. We propose token masking regularization, a simple yet the…
AttributeClassificationLanguage IdentificationSentiment Analysis+2Advancing Uto-Aztecan Language Technologies: A Case Study on the Endangered Comanche Language
The digital exclusion of endangered languages remains a critical challenge in NLP, limiting both linguistic research and revitalization efforts. This study introduces the first computational investigation of Comanche, an…
Language IdentificationSynthetic Data GenerationImproving Informally Romanized Language Identification
The Latin script is often used to informally write languages with non-Latin native scripts. In many cases (e.g., most languages in India), there is no conventional spelling of words in the Latin script, hence there will …
Language Identification(Im)possibility of Automated Hallucination Detection in Large Language Models
Is automated hallucination detection possible? In this work, we introduce a theoretical framework to analyze the feasibility of automatically detecting hallucinations produced by large language models (LLMs). Inspired by…
HallucinationLanguage IdentificationText GenerationCOMI-LINGUA: Expert Annotated Large-Scale Dataset for Multitask NLP in Hindi-English Code-Mixing
The rapid growth of digital communication has driven the widespread use of code-mixing, particularly Hindi-English, in multilingual communities. Existing datasets often focus on romanized text, have limited scope, or rel…
Language Identificationnamed-entity-recognitionNamed Entity RecognitionPart-Of-Speech TaggingKréyoLID From Language Identification Towards Language Mining
Automatic language identification is frequently framed as a multi-class classification problem. However, when creating digital corpora for less commonly written languages, it may be more appropriate to consider it a data…
Language IdentificationMulti-class ClassificationNusaAksara: A Multimodal and Multilingual Benchmark for Preserving Indonesian Indigenous Scripts
Indonesia is rich in languages and scripts. However, most NLP progress has been made using romanized text. In this paper, we present NusaAksara, a novel public benchmark for Indonesian languages that includes their origi…
Image SegmentationLanguage IdentificationOptical Character Recognition (OCR)Semantic Segmentation+1English Please: Evaluating Machine Translation with Large Language Models for Multilingual Bug Reports
Accurate translation of bug reports is critical for efficient collaboration in global software development. In this study, we conduct the first comprehensive evaluation of machine translation (MT) performance on bug repo…
Domain AdaptationLanguage IdentificationMachine TranslationTAG+1Multi-label Scandinavian Language Identification (SLIDE)
Identifying closely related languages at sentence level is difficult, in particular because it is often impossible to assign a sentence to a single language. In this paper, we focus on multi-label sentence-level Scandina…
Language IdentificationSentenceOn the use of Performer and Agent Attention for Spoken Language Identification
One of the methods for language Identification (LID) involves deriving speech representation from pre-trained models using self-supervised learning, followed by fine-tuning the model for the LID task. State-of-the-art ap…
Language IdentificationSelf-Supervised LearningSpoken language identificationEvaluating Standard and Dialectal Frisian ASR: Multilingual Fine-tuning and Language Identification for Improved Low-resource Performance
Automatic Speech Recognition (ASR) performance for low-resource languages is still far behind that of higher-resource languages such as English, due to a lack of sufficient labeled data. State-of-the-art methods deploy s…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Language Identificationspeech-recognition+2Is It Navajo? Accurate Language Detection in Endangered Athabaskan Languages
Endangered languages, such as Navajo - the most widely spoken Native American language - are significantly underrepresented in contemporary language technologies, exacerbating the challenges of their preservation and rev…
DiversityLanguage IdentificationLanguage ModelingLanguage Modelling+1Fleurs-SLU: A Massively Multilingual Benchmark for Spoken Language Understanding
While recent multilingual automatic speech recognition models claim to support thousands of languages, ASR for low-resource languages remains highly unreliable due to limited bimodal speech and text training data. Better…
Automatic Speech RecognitionClassificationintent-classificationIntent Classification+8Indonesian-English Code-Switching Speech Synthesizer Utilizing Multilingual STEN-TTS and Bert LID
Multilingual text-to-speech systems convert text into speech across multiple languages. In many cases, text sentences may contain segments in different languages, a phenomenon known as code-switching. This is particularl…
Language Identificationtext-to-speechText to SpeechEnhancing Code-Switching ASR Leveraging Non-Peaky CTC Loss and Deep Language Posterior Injection
Code-switching-where multilingual speakers alternately switch between languages during conversations-still poses significant challenges to end-to-end (E2E) automatic speech recognition (ASR) systems due to phenomena of b…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Language IdentificationMixture-of-Experts+2Exploring Facets of Language Generation in the Limit
The recent work of Kleinberg & Mullainathan [KM24] provides a concrete model for language generation in the limit: given a sequence of examples from an unknown target language, the goal is to generate new examples from t…
Language IdentificationText Generation