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Table of Contents
Joint Approaches for Sentence Alignment on Multiparallel Texts
Johannes Graën
2016-11-29
Overview
- Sentence Alignment on Multiparallel Texts
- Approaches
- Agreement of Bilingual Alignments
- Sampling in Discrete Vector Space
- Agglomerative Hierarchical Clustering
- Outlook
- Evaluation Metrics
- Hierarchical Clustering for Word Alignment
Sentence Alignment on Multiparallel Texts
- Like sentence alignment of two languages.
- There may be alignments that only exists on a subset of languages.
- This leads to hierarchical alignments.
Example
| de | 1+3 | Es geht nicht um die Großzügigkeit des Präsidenten, es geht um die Zeit, die Sie sich selbst genehmigen; |
| 2+3 | ich habe Ihnen angezeigt, wann die Minute abgelaufen war. | |
| en | 3 | Mr Izquierdo Collado, it is not a question of the President’s generosity. |
| It is a question of the time you allow yourself, because I informed you when your minute was up. | ||
| fr | 1+3 | Monsieur Izquierdo, il ne s’agit pas de la générosité du président, il s’agit du temps que vous vous attribuez. |
| 2+3 | Je vous ai fait signe quand vous avez atteint la minute. |
Agreement of Bilingual Alignments
- Perform sentence alignment on all language pairs.
- Derive correct alignments by “voting”.
- Hypothesis: The majority of pairwise alignments is correct in most cases, i.e. anya alignment error is due to the properties of its particular language pair.
Approach
- Perform pairwise alignments with hunalign.
- Join all these alignments in a graph.
- Calculate “connectedness” by counting supporting languages for each edge.
- How many languages align with both sentences of a particular language pair?
- Continue deleting the least supported edge until small consistent clusters emerge.
- An alignment hierarchy can be obtained by reversing the deletion process.
Two Languages
Three Languages
Four Languages
Five Languages
Hierarchical Alignments
Problems/Limitations
- Short sentences in 1:n pairs do not align in any language.
- … and we are merely removing (wrong) alignments.
- Decisions not straightforward if more than one pair disagrees.
- hunalign's alignment score does not help taking the right decision.
- Dictionaries for hunalign only allow binary entries.
Sampling in Discrete Vector Space
- Discrete vector space spanned by languages as dimensions.
- Alignments are pairs of location and direction vectors with all positive components.
- E.g. $\left((1,2)^T,(2,1)^T\right)$ defines the alignment of the second and third sentence of the first language with the third sentence of the second language.
- The location vector of the nth alignment equals the sum of the direction vector 1..n-1.
- Alignment is obtained by simulated annealing.
Visual Representation
Approach
- Set initial aligment to a sequence of vectors approximating a diagonal line.
- Calculate local (pairwise) and global alignment scores (and keep results in memory).
- Find and evaluate all applicable sampling operations.
- Sample by selecting one of those operations – according to their respective evaluation scores.
- Lower temperature, i.e. probability of picking an operation that leads to a worse sample.
- Repeat from (3) until temperature reaches zero-point.
Sampling Operations
- Changing two consecutive vectors $\vec{x}$ and $\vec{y}$ such that $\vec{x}^\prime + \vec{y}^\prime = \vec{x} + \vec{y}$.
- Replace two consecutive vectors $\vec{x}$ and $\vec{y}$ by vector $\vec{z}$ such that $\vec{z} = \vec{x} + \vec{y}$.
- Split a vector $\vec{z}$ into vectors $\vec{x}$ and $\vec{y}$ such that $\vec{x} + \vec{y} = \vec{z}$.
Problems/Limitations
- The sampling often does not converge.
- For higher dimensions (more languages), sampling did not inlcude the correct (gold) alignment.
- Finding and evaluation all applicable operations is expensive, even if scores are only calculated on language pairs.
