Guhindura imashini
Machine translation is automated conversion from a source language to a target language.
Incamake
Neural systems often treat this as a sequence-to-sequence task: read one sequence and produce another. Building and evaluating such a system requires attention to data alignment and language-specific errors.
Ibyingenzi byingenzi
- Check aligned data and document-level splits.
- Record evaluation configuration.
- Inspect meaning-changing errors by language pair.
Kwibira cyane
Parallel training data pairs source passages with corresponding translations. Incorrect alignment, duplicated material, or mismatched language labels can teach the wrong relationship. Clean the pairs and keep documents together when splitting evaluation data to avoid near-duplicate leakage. Tokenization determines how text becomes model inputs. A tokenizer that handles one writing system efficiently may split another into many more units. Check the length limits in both languages and whether truncation removes the end of either the source or target passage. Automatic metrics make repeated experiments practical. BLEU compares patterns of word sequences with reference translations, but a metric is not a complete judgment of meaning, readability, or suitability for a domain. Evaluation settings and reference choices matter, so record them with the score. Use an error taxonomy alongside metrics: additions, omissions, changed numbers, inconsistent terminology, incorrect negation, and awkward phrasing. Assess each language pair and domain separately. An average across several well-resourced languages can conceal failures in a less-represented language or specialized document type.
Ubushishozi
A sentence may have several valid translations. Low surface overlap with one reference does not necessarily imply incorrect meaning, while high overlap can still conceal a critical changed word.
Compare usefulness with word overlap
- Imagine a reference “The package did not arrive.” Candidate A says “The parcel never arrived.” Candidate B says “The package did arrive.”
- Candidate A uses different words but preserves the main meaning. Candidate B resembles the reference while reversing the outcome.
- Record the negation error explicitly instead of choosing a translation by appearance or overlap alone.
The constructed example demonstrates why metric-based comparisons need semantic review.
Ingaruka z'Ingamba
Umuvuduko n'igipimo
Ururimi rwakazi rushobora kugenda byihuse nta gutamba guhuzagurika.
Kugera no kugera
Yagura uburyo bwindimi nuburyo bwo gutumanaho.
Ibyemezo bisobanutse
Amakipe arashobora kumara umwanya munini murubanza mugihe automatike ikora gusubiramo.
Gushyira mu bikorwa Isi
Evaluate a fixed test set with both a documented metric and bilingual error review.
Audit source-target pairs for mismatched dates, names, and sentence boundaries.
Ingaruka & Kurinda
Ibintu bifatika bishobora kwinjiza bucece raporo, gushyigikira imigendekere, cyangwa ibisubizo byubushakashatsi.
Kwihuta byihuse birashobora gukora ibisubizo bidahuye mubisabwa bisa.
Ibyanditswe byumvikana birashobora kugaragara niba kugenzura kugenzura ari ntege.
Igishushanyo mbonera
Sobanura imiterere isohoka, amajwi, hamwe nubuziranenge mbere yo gutangira.
Ibisubizo byibanze hamwe nisoko yizewe igihe cyose ukuri kwingirakamaro.
Komeza kugenzura abantu kugenzura ibisubizo byinshi.
Kurikirana uburyo bwo kunanirwa no kongera imyitozo cyangwa akazi gahoraho.
Inkomoko no gusoma
- Association for Computational LinguisticsBleu: a Method for Automatic Evaluation of Machine Translation
Komeza Ubushakashatsi
Free newsletter
Get the daily AI briefing
Three verified AI stories every weekday morning, written in plain English. Free forever, no ads.
One email each weekday. Unsubscribe in one click. We never sell or share your address.
Test yourself
Take the Machine Translation quiz
Instant feedback on every answer, and a shareable certificate with a verifiable ID once you pass a course.
Support free AI education. AI Understanding is a 501(c)(3) nonprofit — no ads, no paywall, ever. Make a donation
Ubuyobozi bukurikira
Ubuhinduzi bwa AI
Ibibazo bikunze kubazwa
Is BLEU a percentage of correctly translated sentences?
No. It is an automatic reference-based metric, not a direct count of sentences that a human would judge correct.