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Found 32 papers, 8 papers with code
Boring Problems Are Sometimes the Most Interesting
In a recent position paper, Turing Award Winners Yoshua Bengio, Geoffrey Hinton, and Yann LeCun make the case that symbolic methods are not needed in AI and that, while there are still many issues to be resolved, AI will be solved using purely neural methods.
The Taxonomy of Writing Systems: How to Measure How Logographic a System Is
Our work provides the first quantifiable measure of the notion of logography that accords with linguistic intuition and, we argue, provides better insight into what this notion means.
Mockingbird at the SIGTYP 2022 Shared Task: Two Types of Models forthe Prediction of Cognate Reflexes
For reflex generation, the missing reflexes are treated as “masked pixels” in an “image” which is a representation of an entire cognate set across a language family.
BiPhone: Modeling Inter Language Phonetic Influences in Text
To the best of our knowledge, FunGLUE is the first benchmark to introduce L1-L2 interactions in text.
Lenient Evaluation of Japanese Speech Recognition: Modeling Naturally Occurring Spelling Inconsistency
Word error rate (WER) and character error rate (CER) are standard metrics in Speech Recognition (ASR), but one problem has always been alternative spellings: If one's system transcribes adviser whereas the ground truth has advisor, this will count as an error even though the two spellings really represent the same word.
Beyond Arabic: Software for Perso-Arabic Script Manipulation
This paper presents an open-source software library that provides a set of finite-state transducer (FST) components and corresponding utilities for manipulating the writing systems of languages that use the Perso-Arabic script.
Graphemic Normalization of the Perso-Arabic Script
Since its original appearance in 1991, the Perso-Arabic script representation in Unicode has grown from 169 to over 440 atomic isolated characters spread over several code pages representing standard letters, various diacritics and punctuation for the original Arabic and numerous other regional orthographic traditions.
Helpful Neighbors: Leveraging Neighbors in Geographic Feature Pronunciation
If one sees the place name Houston Mercer Dog Run in New York, how does one know how to pronounce it?
Structured abbreviation expansion in context
Ad hoc abbreviations are commonly found in informal communication channels that favor shorter messages.
Semi-supervised URL Segmentation with Recurrent Neural Networks Pre-trained on Knowledge Graph Entities
Breaking domain names such as openresearch into component words open and research is important for applications like Text-to-Speech synthesis and web search.
Semi-supervised URL Segmentation with Recurrent Neural NetworksPre-trained on Knowledge Graph Entities
Breaking domain names such as openresearch into component words open and research is important for applications like Text-to-Speech synthesis and web search.
Google Crowdsourced Speech Corpora and Related Open-Source Resources for Low-Resource Languages and Dialects: An Overview
This paper presents an overview of a program designed to address the growing need for developing freely available speech resources for under-represented languages.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
NEMO: Frequentist Inference Approach to Constrained Linguistic Typology Feature Prediction in SIGTYP 2020 Shared Task
This paper describes the NEMO submission to SIGTYP 2020 shared task which deals with prediction of linguistic typological features for multiple languages using the data derived from World Atlas of Language Structures (WALS).
Neural Models of Text Normalization for Speech Applications
One problem that has been somewhat resistant to effective machine learning solutions is text normalization for speech applications such as text-to-speech synthesis (TTS).
Automatic Ambiguity Detection
Most work on sense disambiguation presumes that one knows beforehand -- e. g. from a thesaurus -- a set of polysemous terms.
Fast and Accurate Reordering with ITG Transition RNN
Compared to a strong baseline of attention-based RNN, our ITG RNN re-ordering model can reach the same reordering accuracy with only 1/10 of the training data and is 2. 5x faster in decoding.
RNN Approaches to Text Normalization: A Challenge
Though our conclusions are largely negative on this point, we are actually not arguing that the text normalization problem is intractable using an pure RNN approach, merely that it is not going to be something that can be solved merely by having huge amounts of annotated text data and feeding that to a general RNN model.
Minimally Supervised Written-to-Spoken Text Normalization
In speech-applications such as text-to-speech (TTS) or automatic speech recognition (ASR), \emph{text normalization} refers to the task of converting from a \emph{written} representation into a representation of how the text is to be \emph{spoken}.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
TTS for Low Resource Languages: A Bangla Synthesizer
We present a text-to-speech (TTS) system designed for the dialect of Bengali spoken in Bangladesh.
Minimally Supervised Number Normalization
We propose two models for verbalizing numbers, a key component in speech recognition and synthesis systems.
A Database for Measuring Linguistic Information Content
But it is a question that seems as if it ought to have an answer.
