Papers by Ebrahim Ansari

4 papers
ELITR Multilingual Live Subtitling: Demo and Strategy (2021.eacl-demos)

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Challenge: Using a prototype, we present an automatic speech translation system for live subtitling of conference speech . the system is routinely tested in recognizing English, Czech, and German speech - and presenting it simultaneously into 42 target languages.
Approach: They propose an automatic speech translation system aimed at live subtitling of conference presentations.
Outcome: The proposed system is a working prototype that is routinely tested in recognizing English, Czech, and German speech and presenting it translated simultaneously into 42 target languages.
Extracting an English-Persian Parallel Corpus from Comparable Corpora (L18-1)

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Challenge: Existing methods to extract parallel sentences from Wikipedia are limited for some language pairs such as Persian-English.
Approach: They propose a bidirectional method to extract parallel sentences from Wikipedia . they add extracted sentences to existing training data and use IR system to measure similarity .
Outcome: The proposed method outperforms the one-directional approach in analyzing translation data from two translation systems and IR systems.
LSCP: Enhanced Large Scale Colloquial Persian Language Understanding (2020.lrec-1)

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Challenge: a gap exists in describing low-resource formal languages such as Persian . a large scale corpus of 120M sentences is proposed to fill this gap .
Approach: They propose to target a gap in describing the colloquial language for low-resource ones such as Persian . a large scale Persian corpus is hierarchically organized in a semantic taxonomy .
Outcome: The proposed corpus consists of 120M sentences from 27M tweets annotated with parsing tree, part-of-speech tags, sentiment polarity and translation in five different languages.
SLTEV: Comprehensive Evaluation of Spoken Language Translation (2021.eacl-demos)

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Challenge: Spoken Language Translation (SLT) evaluation of machine translation (MT) quality has been investigated for decades.
Approach: They propose an open-source tool for assessing machine translation (MT) quality based on time-stamped transcripts and reference translations.
Outcome: The proposed evaluation tool is based on time-stamped transcripts and reference translations into a target language.

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