Papers Text Normalization
“Text Normalization” 태그가 달린 논문 145편 · 필터 해제
Dynamic Context-Aware Streaming Pretrained Language Model For Inverse Text Normalization
Inverse Text Normalization (ITN) is crucial for converting spoken Automatic Speech Recognition (ASR) outputs into well-formatted written text, enhancing both readability and usability. Despite its importance, the integra…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Language ModelingLanguage Modelling+3Visualizing Public Opinion on X: A Real-Time Sentiment Dashboard Using VADER and DistilBERT
In the age of social media, understanding public sentiment toward major corporations is crucial for investors, policymakers, and researchers. This paper presents a comprehensive sentiment analysis system tailored for cor…
Sentiment AnalysisSentiment ClassificationText NormalizationChain of Correction for Full-text Speech Recognition with Large Language Models
Full-text error correction with Large Language Models (LLMs) for Automatic Speech Recognition (ASR) has gained increased attention due to its potential to correct errors across long contexts and address a broader spectru…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Punctuation Restorationspeech-recognition+2Misspellings in Natural Language Processing: A survey
This survey provides an overview of the challenges of misspellings in natural language processing (NLP). While often unintentional, misspellings have become ubiquitous in digital communication, especially with the prolif…
Data AugmentationMachine TranslationSurveytext-classification+2Universal-2-TF: Robust All-Neural Text Formatting for ASR
This paper introduces an all-neural text formatting (TF) model designed for commercial automatic speech recognition (ASR) systems, encompassing punctuation restoration (PR), truecasing, and inverse text normalization (IT…
AllAutomatic Speech RecognitionAutomatic Speech Recognition (ASR)Computational Efficiency+4Digestion Algorithm in Hierarchical Symbolic Forests: A Fast Text Normalization Algorithm and Semantic Parsing Framework for Specific Scenarios and Lightweight Deployment
Text Normalization and Semantic Parsing have numerous applications in natural language processing, such as natural language programming, paraphrasing, data augmentation, constructing expert systems, text matching, and mo…
Lightweight DeploymentSemantic ParsingText NormalizationNeural Text Normalization for Luxembourgish using Real-Life Variation Data
Orthographic variation is very common in Luxembourgish texts due to the absence of a fully-fledged standard variety. Additionally, developing NLP tools for Luxembourgish is a difficult task given the lack of annotated an…
Text NormalizationMachine Learning Driven Smishing Detection Framework for Mobile Security
The increasing reliance on smartphones for communication, financial transactions, and personal data management has made them prime targets for cyberattacks, particularly smishing, a sophisticated variant of phishing cond…
ManagementMobile SecurityText NormalizationHybrid Deep Learning for Legal Text Analysis: Predicting Punishment Durations in Indonesian Court Rulings
Limited public understanding of legal processes and inconsistent verdicts in the Indonesian court system led to widespread dissatisfaction and increased stress on judges. This study addresses these issues by developing a…
Computational EfficiencyDocument SummarizationSentenceText NormalizationWER We Stand: Benchmarking Urdu ASR Models
This paper presents a comprehensive evaluation of Urdu Automatic Speech Recognition (ASR) models. We analyze the performance of three ASR model families: Whisper, MMS, and Seamless-M4T using Word Error Rate (WER), along …
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Benchmarkingspeech-recognition+2Full-text Error Correction for Chinese Speech Recognition with Large Language Model
Large Language Models (LLMs) have demonstrated substantial potential for error correction in Automatic Speech Recognition (ASR). However, most research focuses on utterances from short-duration speech recordings, which a…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Language ModelingLanguage Modelling+9What is lost in Normalization? Exploring Pitfalls in Multilingual ASR Model Evaluations
This paper explores the pitfalls in evaluating multilingual automatic speech recognition (ASR) models, with a particular focus on Indic language scripts. We investigate the text normalization routine employed by leading …
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)speech-recognitionSpeech Recognition+2Historical German Text Normalization Using Type- and Token-Based Language Modeling
Historic variations of spelling poses a challenge for full-text search or natural language processing on historical digitized texts. To minimize the gap between the historic orthography and contemporary spelling, usually…
DecoderLanguage ModelingLanguage ModellingLarge Language Model+2Is text normalization relevant for classifying medieval charters?
This study examines the impact of historical text normalization on the classification of medieval charters, specifically focusing on document dating and locating. Using a data set of Middle High German charters from a di…
Document DatingText NormalizationPositional Description for Numerical Normalization
We present a Positional Description Scheme (PDS) tailored for digit sequences, integrating placeholder value information for each digit. Given the structural limitations of subword tokenization algorithms, language model…
speech-recognitionSpeech RecognitionText Normalizationtext-to-speech+1The CHiME-8 DASR Challenge for Generalizable and Array Agnostic Distant Automatic Speech Recognition and Diarization
This paper presents the CHiME-8 DASR challenge which carries on from the previous edition CHiME-7 DASR (C7DASR) and the past CHiME-6 challenge. It focuses on joint multi-channel distant speech recognition (DASR) and diar…
Automatic Speech RecognitionDistant Speech Recognitionspeech-recognitionSpeech Recognition+1Exploiting Dialect Identification in Automatic Dialectal Text Normalization
Dialectal Arabic is the primary spoken language used by native Arabic speakers in daily communication. The rise of social media platforms has notably expanded its use as a written language. However, Arabic dialects do no…
Dialect IdentificationText NormalizationPrior-agnostic Multi-scale Contrastive Text-Audio Pre-training for Parallelized TTS Frontend Modeling
Over the past decade, a series of unflagging efforts have been dedicated to developing highly expressive and controllable text-to-speech (TTS) systems. In general, the holistic TTS comprises two interconnected components…
Polyphone disambiguationText Normalizationtext-to-speechText to SpeechVNLP: Turkish NLP Package
In this work, we present VNLP: the first dedicated, complete, open-source, well-documented, lightweight, production-ready, state-of-the-art Natural Language Processing (NLP) package for the Turkish language. It contains …
Morphological Analysisnamed-entity-recognitionNamed Entity RecognitionPart-Of-Speech Tagging+6Multi-Task Learning for Front-End Text Processing in TTS
We propose a multi-task learning (MTL) model for jointly performing three tasks that are commonly solved in a text-to-speech (TTS) front-end: text normalization (TN), part-of-speech (POS) tagging, and homograph disambigu…
Language ModelingLanguage ModellingMulti-Task LearningPart-Of-Speech Tagging+5