Search Results for author:
Found 25 papers, 6 papers with code
Benchmarking: Past, Present and Future
There used to be more top-down leadership from government (and industry, in the case of systems, with benchmarks such as SPEC).
Reflections on 30 Years of Language Resource Development and Sharing
The Linguistic Data Consortium was founded in 1992 to solve the problem that limitations in access to shareable data was impeding progress in Human Language Technology research and development.
GRAIL—Generalized Representation and Aggregation of Information Layers
This paper identifies novel characteristics necessary to successfully represent multiple streams of natural language information from speech and text simultaneously, and proposes a multi-tiered system that implements these characteristics centered around a declarative configuration.
Using Mixed Incentives to Document Xi’an Guanzhong
This paper describes our use of mixed incentives and the citizen science portal LanguageARC to prepare, collect and quality control a large corpus of object namings for the purpose of providing speech data to document the under-represented Guanzhong dialect of Chinese spoken in the Shaanxi province in the environs of Xi’an.
The NIEUW Project: Developing Language Resources through Novel Incentives
NIEUW leverages the power of novel incentives to elicit linguistic data and annotations from a wide variety of contributors including citizen scientists, game players, and language students and professionals.
Identifying stable speech-language markers of autism in children: Preliminary evidence from a longitudinal telephony-based study
This study examined differences in linguistic features produced by autistic and neurotypical (NT) children during brief picture descriptions, and assessed feature stability over time.
Automatic recognition of suprasegmentals in speech
This study reports our efforts to improve automatic recognition of suprasegmentals by fine-tuning wav2vec 2. 0 with CTC, a method that has been successful in automatic speech recognition.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
The Third DIHARD Diarization Challenge
DIHARD III was the third in a series of speaker diarization challenges intended to improve the robustness of diarization systems to variability in recording equipment, noise conditions, and conversational domain.
Neural Representations for Modeling Variation in Speech
We show that speech representations extracted from a specific type of neural model (i. e. Transformers) lead to a better match with human perception than two earlier approaches on the basis of phonetic transcriptions and MFCC-based acoustic features.
Probing Acoustic Representations for Phonetic Properties
Pre-trained acoustic representations such as wav2vec and DeCoAR have attained impressive word error rates (WER) for speech recognition benchmarks, particularly when labeled data is limited.
LanguageARC: Developing Language Resources Through Citizen Linguistics
Like other Citizen Science platforms and projects, LanguageARC harnesses the power and efforts of volunteers who are motivated by the incentives of contributing to science, learning and discovery, and belonging to a community dedicated to social improvement.
A Progress Report on Activities at the Linguistic Data Consortium Benefitting the LREC Community
This latest in a series of Linguistic Data Consortium (LDC) progress reports to the LREC community does not describe any single language resource, evaluation campaign or technology but sketches the activities, since the last report, of a data center devoted to supporting the work of LREC attendees among other research communities.
The Second DIHARD Diarization Challenge: Dataset, task, and baselines
This paper introduces the second DIHARD challenge, the second in a series of speaker diarization challenges intended to improve the robustness of diarization systems to variation in recording equipment, noise conditions, and conversational domain.
From Human Language Technology to Human Language Science
Thirty years ago, in order to get past roadblocks in Machine Translation and Automatic Speech Recognition, DARPA invented a new way to organize and manage technological R{\&}D : a {``}common task{''} is defined by a formal quantitative evaluation metric and a body of shared training data, and researchers join an open competition to compare approaches.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Building Language Resources for Exploring Autism Spectrum Disorders
Autism spectrum disorder (ASD) is a complex neurodevelopmental condition that would benefit from low-cost and reliable improvements to screening and diagnosis.
New Directions for Language Resource Development and Distribution
Despite the growth in the number of linguistic data centers around the world, their accomplishments and expansions and the advances they have help enable, the language resources that exist are a small fraction of those required to meet the goals of Human Language Technologies (HLT) for the worldÂ’s languages and the promises they offer: broad access to knowledge, direct communication across language boundaries and engagement in a global community.
Twenty Years of Language Resource Development and Distribution: A Progress Report on LDC Activities
On the Linguistic Data Consortium's (LDC) 20th anniversary, this paper describes the changes to the language resource landscape over the past two decades, how LDC has adjusted its practice to adapt to them and how the business model continues to grow.
Annotation graphs as a framework for multidimensional linguistic data analysis
In recent work we have presented a formal framework for linguistic annotation based on labeled acyclic digraphs.
