Transliteration pair acquisition has received significant attention as a technique for constructing up-to-date transliteration lexicons, and for supporting machine translation and cross-language information retrieval. Previous studies on transliteration pair acquisition focused on only the phonetic similarity model but seldom considered the real-usage of transliterations in texts. Moreover, previous web-based validation models considered only one-way validation (validation from the viewpoint of a source term) rather than joint validation between a source term and a target term. To address these problems, we propose a novel transliteration pair acquisition model that extracts transliteration pairs from the Web and validates the pairs by combining the phonetic similarity and joint web-validation models. Experiments demonstrated that our transliteration pair acquisition model was effective.