Machine Translations. Linguistic characteristics of MT by John Lehrberger

By John Lehrberger

Using the pc in translating traditional languages levels from that of a translator's relief for notice processing and dictionary look-up to that of a full-fledged translator by itself. but the stumbling blocks to translating via the pc are basically linguistic. to beat them it can be crucial to unravel the ambiguities that pervade a typical language while phrases and sentences are considered in isolation. the matter then is to formalize, within the machine, those features of normal language figuring out. during this paintings the authors exhibit how, from a linguistic standpoint, one might shape a few thought of what is going on within a system's black field, given simply the enter (original textual content) and the uncooked output (translated textual content prior to post-editing). Many examples of English/French translation are used to demonstrate the foundations concerned.

Show description

Read Online or Download Machine Translations. Linguistic characteristics of MT systems PDF

Similar ai & machine learning books

Artificial Intelligence Through Prolog

Synthetic Intelligence via Prolog ebook

Language, Cohesion and Form (Studies in Natural Language Processing)

As a pioneer in computational linguistics, operating within the earliest days of language processing by way of desktop, Margaret Masterman believed that that means, no longer grammar, was once the major to knowing languages, and that machines may perhaps be sure the which means of sentences. This quantity brings jointly Masterman's groundbreaking papers for the 1st time, demonstrating the significance of her paintings within the philosophy of technology and the character of iconic languages.

Handbook of Natural Language Processing

This research explores the layout and alertness of usual language text-based processing structures, in keeping with generative linguistics, empirical copus research, and synthetic neural networks. It emphasizes the sensible instruments to house the chosen process

Additional info for Machine Translations. Linguistic characteristics of MT systems

Example text

K) Cutoff of the power law changes with array size used for analysis, and thus reflects the limitation of the observation window. Broken line: slope of power law −3/2 as guide to the eye. 13 14 2 Criticality in Cortex: Neuronal Avalanches and Coherence Potentials and therefore the question arises why such temporal discretization is required in the first place. , [84]). In the case of real cortical networks and given current technology, though, population activity, such as captured in the LFP, can only be sampled in spatially discrete locations.

B) Corresponding relationships describe the 1 101 1 10 2 10 3 Main avalanche size s (μV) organization of neuronal avalanches. 5 (n = 6 slowly rocked cortex cultures). Middle: Decay in avalanche probability following a main avalanche. The power law with slope of −1 does not depend on the trigger avalanche size s (single cortex culture). 7d; triangles: awake macaque monkeys; broken line: slope of −1). For further details, see [34]. processing through cascading activity, the dynamical concepts of oscillations and neuronal avalanches need to be reconciled.

Note slope of −3/2 (broken line) at optimal dopamine D1 receptor stimulation and cutoff (arrow; for details, see [72]. (b) Spontaneous neuronal avalanches in early differentiated superficial layers in the rat in vivo. 4 mm −2 10 10 600 27 −3/2 1 mm 10 100 Avalanche size sLFP (μV) 10 0 PM 2 (b) Resting activity, awake macaque monkey (LFP) P(s) 16 0 1 10 10 Avalanche size ssensor (n) 2 day 13). Right: Corresponding power law in neuronal avalanche sizes (for details, see [81]). (c) Neuronal avalanches in the awake macaque monkey.

Download PDF sample

Rated 4.72 of 5 – based on 6 votes