Preparing an Endangered Language for the Digital Age: The Case of Judeo-Spanish
Abstract
Domain fit: AI-core · Core AI workload signals detected from paper context and implementation/artifact evidence.
We develop machine translation and speech synthesis systems to complement the efforts of revitalizing Judeo-Spanish, the exiled language of Sephardic Jews, which survived for centuries, but now faces the threat of extinction in the digital age. Building on resources created by the Sephardic community of Turkey and elsewhere, we create corpora and tools that would help preserve this language for future generations. For machine translation, we first develop a Spanish to Judeo-Spanish rule-based machine translation system, in order to generate large volumes of synthetic parallel data in the relevant language pairs: Turkish, English and Spanish. Then, we train baseline neural machine translation engines using this synthetic data and authentic parallel data created from translations by the Sephardic community. For text-to-speech synthesis, we present a 3.5 hour single speaker speech corpus for building a neural speech synthesis engine. Resources, model weights and online inference engines are shared publicly.
Results and benchmarks
We develop machine translation and speech synthesis systems to complement the efforts of revitalizing Judeo-Spanish, the exiled language of Sephardic Jews, which survived for centuries, but now faces the threat of extinction in the digital age.
Benchmark evidence is limited
Evidence graph: 3 refs, 3 links.
Utility signals: depth 70/100, grounding 75/100, status medium.
Implementation
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Time to first repro: a few days
Spacial/csstuff is the closest maintained adjacent implementation (Matches contextual method/domain keyword: computer science). It is not paper-verified; validate algorithm and evaluation setup against the paper before trusting reported metrics. Community adoption signal: 85 GitHub stars.
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Reproduction readiness
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Hardware requirements
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Validation caveat
Framework baselines
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Repositories and ecosystem
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- Spacial/csstuff Adjacent · Confidence: Low · 85 stars
Matches contextual method/domain keyword: computer science
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Hugging Face artifacts
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Research context
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Citations
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References
Tasks
Turkish, Machine translation, Computer science, Inference, Mandarin Chinese, Wizard of oz, Linguistics
Methods
Transformer
Domains
Natural language processing, Artificial intelligence, Speech synthesis, Speech recognition
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