Polyhedral results for position based scheduling of chains on a single machine

We consider a scheduling problem where a set of unit-time jobs have to be sequenced on a single machine without any idle times between the jobs. Preemption of processing is not allowed. The processing cost of a job is determined by the position in the sequence, i.e., for each job and each position, there is an associated weight, and one has to determine a sequence of jobs which minimizes the total weight incurred by the positions of the jobs. In addition, the ordering of the jobs must satisfy the given chain precedence constraints. In this paper we investigate the polyhedron associated with a special case of the problem where each\ud chain has length two. We show that optimizing over this polyhedron is strongly NP-hard, however, we present a class of facet-defining inequalities along with a polynomial-time separation procedure. We generalize these results to the case of chains with lengths at most two. Finally, we present our computational results that show that separating these inequalities can significantly improve a linear programming based branch-and-bound procedure to solve the problem

Multi-criteria approximation schemes for the resource constrained shortest path problem

In the resource constrained shortest path problem we are given a directed graph along with a source node and a destination node, and each arc has a cost and a vector of weights specifying its requirements from a set of resources with finite budget limits. A minimum cost source-destination path is sought such that the total consumption of the arcs from each resource does not exceed its budget limit. In the case of constant number of weight functions we give a fully polynomial time multi-criteria approximation scheme for the problem which returns a source-destination path of cost at most the optimum, however, the path may slightly violate the budget limits. On the negative side, we show that there does not exist polynomial time multi-criteria approximation scheme for the problem if the number of weight functions is not a constant. The latter result applies to a broad class of problem as well, including the multi-dimensional knapsack, the multi-budgeted spanning tree, the multi-budgeted matroid basis and the multi-budgeted bipartite perfect matching problems

Speech Synthesis from Text and Ultrasound Tongue Image-based Articulatory Input

Articulatory information has been shown to be effective in improving the performance of HMM-based and DNN-based text-to-speech synthesis. Speech synthesis research focuses traditionally on text-to-speech conversion, when the input is text or an estimated linguistic representation, and the target is synthesized speech. However, a research field that has risen in the last decade is articulation-to-speech synthesis (with a target application of a Silent Speech Interface, SSI), when the goal is to synthesize speech from some representation of the movement of the articulatory organs. In this paper, we extend traditional (vocoder-based) DNN-TTS with articulatory input, estimated from ultrasound tongue images. We compare text-only, ultrasound-only, and combined inputs. Using data from eight speakers, we show that that the combined text and articulatory input can have advantages in limited-data scenarios, namely, it may increase the naturalness of synthesized speech compared to single text input. Besides, we analyze the ultrasound tongue recordings of several speakers, and show that misalignments in the ultrasound transducer positioning can have a negative effect on the final synthesis performance.Comment: accepted at SSW11 (11th Speech Synthesis Workshop

Az automatikus irreguláriszönge-detekció sikeressége az irregularitás mintázatának függvényében magyar, spontán és olvasott beszédben

Az automatikus irreguláriszönge-detekció problémája előtérbe került az utóbbi évtizedekben. A jelen kutatásban a [10] algoritmust futtattuk le az irreguláris zönge előfordulásaira manuálisan felcímkézett, magyar nyelvű spontán és felolvasott beszédkorpuszokon, és azt vizsgáltuk, hogy 1. Mennyire pontos a pusztán akusztikai kulcsokon alapuló gépi detekció, és mennyire pontos az akusztikai és percepciós paramétereket egyaránt figyelembe vevő humán annotáció? 2. Milyen tényezők befolyásolják (rontják) az irreguláris zönge detekciójának sikerességét a gépi és a humán annotációkban? Eredményeink szerint az irregularitás általános célú annotációjára folyamatos szövegekben az automata algoritmus nagy hatásfokkal alkalmazható, mivel az előfordulások több mint 90%-át pontosan jelöli. A magánhangzók vizsgálatára létrehozott korpuszokban a gégezárhang figyelmen kívül hagyása miatt kevésbé pontos az automata detekció. Összességében az irregularitás alkalmazott definíciójától függ a gépi detektáló módszer hatásfoka