Papers Text Normalization
“Text Normalization” 태그가 달린 논문 145편 · 필터 해제
indic-punct: An automatic punctuation restoration and inverse text normalization framework for Indic languages
Automatic Speech Recognition (ASR) generates text which is most of the times devoid of any punctuation. Absence of punctuation is text can affect readability. Also, down stream NLP tasks such as sentiment analysis, machi…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Machine TranslationPunctuation Restoration+6Shallow Fusion of Weighted Finite-State Transducer and Language Model for Text Normalization
Text normalization (TN) systems in production are largely rule-based using weighted finite-state transducers (WFST). However, WFST-based systems struggle with ambiguous input when the normalized form is context-dependent…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Language ModelingLanguage Modelling+3Seq-2-Seq based Refinement of ASR Output for Spoken Name Capture
Person name capture from human speech is a difficult task in human-machine conversations. In this paper, we propose a novel approach to capture the person names from the caller utterances in response to the prompt "say a…
Text NormalizationTransformer-based Models of Text Normalization for Speech Applications
Text normalization, or the process of transforming text into a consistent, canonical form, is crucial for speech applications such as text-to-speech synthesis (TTS). In TTS, the system must decide whether to verbalize "1…
SentenceSpeech SynthesisText Normalizationtext-to-speech+2SciCap: Generating Captions for Scientific Figures
Researchers use figures to communicate rich, complex information in scientific papers. The captions of these figures are critical to conveying effective messages. However, low-quality figure captions commonly occur in sc…
ArticlesImage CaptioningText NormalizationSLAM: A Unified Encoder for Speech and Language Modeling via Speech-Text Joint Pre-Training
Unsupervised pre-training is now the predominant approach for both text and speech understanding. Self-attention models pre-trained on large amounts of unannotated data have been hugely successful when fine-tuned on down…
Language ModelingLanguage ModellingText MatchingText Normalization+2A Fast Randomized Algorithm for Massive Text Normalization
Many popular machine learning techniques in natural language processing and data mining rely heavily on high-quality text sources. However real-world text datasets contain a significant amount of spelling errors and impr…
Text NormalizationThe Impact of Text Normalization on Multiword Expressions Discovery in Persian
This paper evaluates normalization procedures of Persian text for a downstream NLP task - multiword expressions (MWEs) discovery. We discuss the challenges the Persian language poses for NLP and evaluate open-source tool…
Text NormalizationA Unified Transformer-based Framework for Duplex Text Normalization
Text normalization (TN) and inverse text normalization (ITN) are essential preprocessing and postprocessing steps for text-to-speech synthesis and automatic speech recognition, respectively. Many methods have been propos…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Data AugmentationSentence+7HUI-Audio-Corpus-German: A high quality TTS dataset
The increasing availability of audio data on the internet lead to a multitude of datasets for development and training of text to speech applications, based on neural networks. Highly differing quality of voice, low samp…
Text Normalizationtext-to-speechText to SpeechVocal Bursts Intensity PredictionBDKG at MEDIQA 2021: System Report for the Radiology Report Summarization Task
This paper presents our winning system at the Radiology Report Summarization track of the MEDIQA 2021 shared task. Radiology report summarization automatically summarizes radiology findings into free-text impressions. Th…
DecoderDomain AdaptationText NormalizationCreating Data in Icelandic for Text Normalization
There is no natural way to acquire normalized data so we try to create good enough data to attempt more advanced methods for text normalization. We manually annotated the first normalized corpus in Icelandic, 40,000 sent…
Text NormalizationAn analysis of full-size Russian complexly NER labelled corpus of Internet user reviews on the drugs based on deep learning and language neural nets
We present the full-size Russian complexly NER-labeled corpus of Internet user reviews, along with an evaluation of accuracy levels reached on this corpus by a set of advanced deep learning neural networks to extract the…
Language ModellingNERRelation ExtractionText NormalizationProteno: Text Normalization with Limited Data for Fast Deployment in Text to Speech Systems
Developing Text Normalization (TN) systems for Text-to-Speech (TTS) on new languages is hard. We propose a novel architecture to facilitate it for multiple languages while using data less than 3% of the size of the data …
Text Normalizationtext-to-speechText to SpeechNeMo Inverse Text Normalization: From Development To Production
Inverse text normalization (ITN) converts spoken-domain automatic speech recognition (ASR) output into written-domain text to improve the readability of the ASR output. Many state-of-the-art ITN systems use hand-written …
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)speech-recognitionSpeech Recognition+1Text Normalization for Low-Resource Languages of Africa
Training data for machine learning models can come from many different sources, which can be of dubious quality. For resource-rich languages like English, there is a lot of data available, so we can afford to throw out t…
Text NormalizationMAPGN: MAsked Pointer-Generator Network for sequence-to-sequence pre-training
This paper presents a self-supervised learning method for pointer-generator networks to improve spoken-text normalization. Spoken-text normalization that converts spoken-style text into style normalized text is becoming …
Machine TranslationSelf-Supervised LearningText NormalizationNeural Inverse Text Normalization
While there have been several contributions exploring state of the art techniques for text normalization, the problem of inverse text normalization (ITN) remains relatively unexplored. The best known approaches leverage …
Text NormalizationAn Unsupervised Normalization Algorithm for Noisy Text: A Case Study for Information Retrieval and Stance Detection
A large fraction of textual data available today contains various types of 'noise', such as OCR noise in digitized documents, noise due to informal writing style of users on microblogging sites, and so on. To enable task…
Information RetrievalOptical Character Recognition (OCR)RetrievalStance Detection+1hinglishNorm - A Corpus of Hindi-English Code Mixed Sentences for Text Normalization
We present hinglishNorm - a human annotated corpus of Hindi-English code-mixed sentences for text normalization task. Each sentence in the corpus is aligned to its corresponding human annotated normalized form. To the be…
SentenceText NormalizationTranslation