10,765 research outputs found
Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the "Speaking Rosetta" JSALT 2017 Workshop
We summarize the accomplishments of a multi-disciplinary workshop exploring
the computational and scientific issues surrounding the discovery of linguistic
units (subwords and words) in a language without orthography. We study the
replacement of orthographic transcriptions by images and/or translated text in
a well-resourced language to help unsupervised discovery from raw speech.Comment: Accepted to ICASSP 201
An Efficient Distribution of Labor in a Two Stage Robust Interpretation Process
Although Minimum Distance Parsing (MDP) offers a theoretically attractive
solution to the problem of extragrammaticality, it is often computationally
infeasible in large scale practical applications. In this paper we present an
alternative approach where the labor is distributed between a more restrictive
partial parser and a repair module. Though two stage approaches have grown in
popularity in recent years because of their efficiency, they have done so at
the cost of requiring hand coded repair heuristics. In contrast, our two stage
approach does not require any hand coded knowledge sources dedicated to repair,
thus making it possible to achieve a similar run time advantage over MDP
without losing the quality of domain independence.Comment: 9 pages, 1 Postscript figure, uses aclap.sty and psfig.tex, In
Proceedings of EMNLP 199
A High Quality Text-To-Speech System Composed of Multiple Neural Networks
While neural networks have been employed to handle several different
text-to-speech tasks, ours is the first system to use neural networks
throughout, for both linguistic and acoustic processing. We divide the
text-to-speech task into three subtasks, a linguistic module mapping from text
to a linguistic representation, an acoustic module mapping from the linguistic
representation to speech, and a video module mapping from the linguistic
representation to animated images. The linguistic module employs a
letter-to-sound neural network and a postlexical neural network. The acoustic
module employs a duration neural network and a phonetic neural network. The
visual neural network is employed in parallel to the acoustic module to drive a
talking head. The use of neural networks that can be retrained on the
characteristics of different voices and languages affords our system a degree
of adaptability and naturalness heretofore unavailable.Comment: Source link (9812006.tar.gz) contains: 1 PostScript file (4 pages)
and 3 WAV audio files. If your system does not support Windows WAV files, try
a tool like "sox" to translate the audio into a format of your choic
Some Requests for Machine Learning Research from the East African Tech Scene
Based on 46 in-depth interviews with scientists, engineers, and CEOs, this
document presents a list of concrete machine research problems, progress on
which would directly benefit tech ventures in East Africa.Comment: Presented at NIPS 2018 Workshop on Machine Learning for the
Developing Worl
Foundation Funding for the Humanities: An Overview of Current and Historical Trends
Foundation Funding for the Humanities: An Overview of Current and Historical Trends, finds that funding for fields such as art history, history and archeology, languages and linguistics, area studies, and the humanistic social sciences increased two and one-half times (149.8 percent) from 335 million in 2002. At the same time the report notes that, despite the overall increase, some scholarly disciplines actually lost ground over the ten year period. Support for the humanities grew more slowly than overall foundation giving during this period (up 199.8 percent), and the share of giving for the humanities slipped from 2.5 percent in the early 1990s to 2.1 percent in 2002
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