The 1762 Arakan earthquake resulted from rupture of the northern Sunda megathrust and is one of those rare preinstrumental earthquakes for which early historical accounts document ground deformations. In order to obtain more comprehensive and detailed measurements of coseismic uplift, we conducted comprehensive field investigations and geochronological analyses of marine terraces on the two largest islands in western Myanmar. We confirm 3–4 m of coseismic coastal emergence along southwestern Cheduba Island, diminishing northeastward to less than 1 m. Farther northeast, uplift associated with the earthquake ranges from slightly more than 1 m to 5–6 m along the western coast of Ramree Island but is insignificant along the island's eastern coast. This double‐hump pattern of uplift coincides with the long‐term anticlinal growth of these two islands. Thus, we propose that the 1762 earthquake resulted from slip on splay faults under the islands, in addition to rupture of the megathrust. Elastic modeling implies that fault slip during the 1762 earthquake ranges from about 9 to 16 m beneath the islands and corresponds to a magnitude of Mw 8.5 if the rupture length of the megathrust is ~500 km. The island's uplift histories suggest recurrence intervals of such events of about 500–700 years. Additional detailed paleoseismological studies would add significant additional detail to the history of large earthquakes in this region.
This paper proposes a novel method for improving query-by-singing/humming systems by using both melody and lyric information. First, singing/humming discrimination is performed to distinguish between singing and humming queries, which is achieved by considering the similarity between acoustic models. For the humming queries, a pitch-only melody recognition method that was ranked first among the MIREX (Music Information Retrieval Evaluation eXchange) query-by-singing/humming task submissions is applied. For the singing queries, a lyric similarity is computed using speech recognition techniques; the computed similarity is subsequently combined with the melody distance to exploit additional information in the lyrics. Several methods for combining melody distance and lyric similarity are investigated. Under the optimal experimental settings, the proposed query-by-singing/humming system achieves 51.19% error rate reduction for the top-10 retrieved results, indicating the feasibility of the proposed method.Index Terms-Combined melody distance and lyric similarity, query-by-singing/humming (QBSH), singing voice recognition, singing/humming discrimination (SHD).
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