Perceptual Continuity and Naturalness of Expressive Strength in Singing Voices Based on Speech Morphing

This paper experimentally shows the importance of perceptual continuity of the expressive strength in vocal timbre for natural change in vocal expression. In order to synthesize various and continuous expressive strengths with vocal timbre, we investigated gradually changing expressions by applying the STRAIGHT speech morphing algorithm to singing voices. Here, a singing voice without expression is used as the base of morphing, and singing voices with three different expressions are used as the target. Through statistical analyses of perceptual evaluations, we confirmed that the proposed morphing algorithm provides perceptual continuity of vocal timbre. Our results showed the following: (i) gradual strengths in absolute evaluations, and (ii) a perceptually linear strength provided by the calculation of corrected intervals of the morph ratio by the inverse (reciprocal) function of an equation that approximates the perceptual strength. Finally, we concluded that applying continuity was highly effective for achieving perceptual naturalness, judging from the results showing that (iii) our gradual transformation method can perform well for perceived naturalness

GPU-Based Optimization of a Free-Viewpoint Video System

We present a method for optimizing the reconstruction and rendering of 3D objects from multiple images by utilizing the latest features of consumer-level graphics hardware based on shader model 4.0. We accelerate visual hull reconstruction by rewriting a shape-from-silhouette algorithm to execute on the GPU's parallel architecture. Rendering a is optimized through the application of geometry shaders to generate billboarding microfacets textured with captured images. We also present a method for handling occlusion in the camera selection process that is optimized for execution on the GPU. Execution time is further improved by rendering intermediate results directly to texture to minimize the number of data transfers between graphics and main memory. We show our GPU based system to be significantly more efficient than a purely CPU-based approach, due to the parallel nature of the GPU, while maintaining graphical quality

Integrated genetic and clinical prognostic factors for aggressive adult T-cell leukemia/lymphoma

成人T細胞白血病リンパ腫（ATL）におけるゲノム情報と臨床情報を統合したリスクモデルを確立 --ATLの個別化医療を推進--. 京都大学プレスリリース. 2023-04-10.The prognosis of aggressive adult T-cell leukemia/lymphoma (ATL) is poor, and allogeneic hematopoietic stem-cell transplantation (allo-HSCT) is a curative treatment. To identify favorable prognostic patients after intensive chemotherapy, and who therefore might not require upfront allo-HSCT, we aimed to improve risk stratification of aggressive ATL patients aged <70 years. The clinical risk factors and genetic mutations were incorporated into risk modeling for overall survival (OS). We generated the m7-ATLPI, a clinicogenetic risk model for OS, that included the ATL prognostic index (PI) (ATL-PI) risk category, and non-silent mutations in seven genes, namely TP53, IRF4, RHOA, PRKCB, CARD11, CCR7, and GATA3. In the training cohort of 99 patients, the m7-ATLPI identified a low-, intermediate-, and high-risk group with 2-year OS of 100%, 43%, and 19%, respectively (hazard ratio [HR] 5.46, p < 0.0001). The m7-ATLPI achieved superior risk stratification compared to the current ATL-PI (C-index 0.92 vs. 0.85, respectively). In the validation cohort of 84 patients, the m7-ATLPI defined low-, intermediate-, and high-risk groups with a 2-year OS of 81%, 30%, and 0%, respectively (HR 2.33, p = 0.0094), and the model again outperformed the ATL-PI (C-index 0.72 vs. 0.70, respectively). The simplified m7-ATLPI, which is easier to use in clinical practice, achieved superior risk stratification compared to the ATL-PI, as did the original m7-ATLPI; the simplified version was calculated by summing the following: high-risk ATL-PI category (+10), low-risk ATL-PI category (−4), and non-silent mutations in TP53 (+4), IRF4 (+3), RHOA (+1), PRKCB (+1), CARD11 (+0.5), CCR7 (−2), and GATA3 (−3)

Structure Sharing Problem And Its Solution In Graph Unification

The revised graph unification algorithms presented here are anore efficient because they reduce the amount of copying that was necessary because of the assmnption that data-structure sharing in inputs occurs only when feature-structure sharing occurs

Strategic Lazy Incremental Copy Graph Unification

The strai, egJc lazy increnmntal copy graph unification method is a combination of two nmLhods for unifying ]&apos;eatufo structures. Olle, called the lazy incremental copy graph unication method, achieves structure sharing with constaa order data access time which reduces the cequired memory. The other, called the strategic incremental copy graph unication mehod, uses an early failure finding strategy which first fries to unify :;ubs[ruc[ures tending to fall in unication; this method is based on stochastic data on Lira likelihood or failure and i&apos;educes unnecessary computation. The combined method makes each featnre structure unification eflicienL and also reduces garbage collection and page swapping occurrences, Lhus increasing the total efficiency of tmLural language processing systems mainly based on I.yped feature structure unification such as natural language analysis and generation systems