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Found 37 papers, 5 papers with code
Fashioning Local Designs from Generic Speech Technologies in an Australian Aboriginal Community
An increasing number of papers have been addressing issues related to low-resource languages and the transcription bottleneck paradigm.
Local Languages, Third Spaces, and other High-Resource Scenarios
How can language technology address the diverse situations of the world’s languages?
Learning From Failure: Data Capture in an Australian Aboriginal Community
Most low resource language technology development is premised on the need to collect data for training statistical models.
A Computational Model for Interactive Transcription
Transcribing low resource languages can be challenging in the absence of a good lexicon and trained transcribers.
Local Word Discovery for Interactive Transcription
Human expertise and the participation of speech communities are essential factors in the success of technologies for low-resource languages.
A Finite State Aproach to Interactive Transcription
We describe a novel approach to transcribing morphologically complex, local, oral languages.
Multiword Expressions and the Low-Resource Scenario from the Perspective of a Local Oral Culture
Research on multiword expressions and on under-resourced languages often begins with problematisation.
Cultural Vocal Bursts Intensity Prediction
speech-recognition
+1
Learning Through Transcription
Transcribing speech for primarily oral, local languages is often a joint effort involving speakers and outsiders.
Phone Based Keyword Spotting for Transcribing Very Low Resource Languages
We investigate the efficiency of two very different spoken term detection approaches for transcription when the available data is insufficient to train a robust speech recognition system.
Sparse Transcription
The transcription bottleneck is often cited as a major obstacle for efforts to document the world’s endangered languages and supply them with language technologies.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Spoken Term Detection Methods for Sparse Transcription in Very Low-resource Settings
We investigate the efficiency of two very different spoken term detection approaches for transcription when the available data is insufficient to train a robust ASR system.
Interactive Word Completion for Morphologically Complex Languages
We show that the space of proximal morph completions is many orders of magnitude smaller than the space of full word completions for Kunwinjku.
Decolonising Speech and Language Technology
After generations of exploitation, Indigenous people often respond negatively to the idea that their languages are data ready for the taking.
Enabling Interactive Transcription in an Indigenous Community
We propose a novel transcription workflow which combines spoken term detection and human-in-the-loop, together with a pilot experiment.
Bootstrapping Techniques for Polysynthetic Morphological Analysis
To address this challenge, we offer linguistically-informed approaches for bootstrapping a neural morphological analyzer, and demonstrate its application to Kunwinjku, a polysynthetic Australian language.
Towards A Robust Morphological Analyzer for Kunwinjku
Kunwinjku is an indigenous Australian language spoken in northern Australia which exhibits agglutinative and polysynthetic properties.
Cross-Lingual Word Embeddings for Low-Resource Language Modeling
We investigate the use of such lexicons to improve language models when textual training data is limited to as few as a thousand sentences.
Multilingual Training of Crosslingual Word Embeddings
Crosslingual word embeddings represent lexical items from different languages using the same vector space, enabling crosslingual transfer.
Learning Crosslingual Word Embeddings without Bilingual Corpora
Crosslingual word embeddings represent lexical items from different languages in the same vector space, enabling transfer of NLP tools.
Bilingual Lexicon Induction
Cross-Lingual Document Classification
+4
NLTK: The Natural Language Toolkit
NLTK, the Natural Language Toolkit, is a suite of open source program modules, tutorials and problem sets, providing ready-to-use computational linguistics courseware.
Ranked #4 on
Multi-Label Text Classification
on CC3M-TagMask
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.
