The acoustic-to-word model based on the Connectionist Temporal Classification (CTC) criterion is a natural end-to-end (E2E) system directly targeting word as output unit. Two issues exist in the system: first, the current output of the CTC model relies on the current input and does not account for context weighted inputs. This is the hard alignment issue.
IEEE SPS Speech and Language Processing Technical Committee Nominations 2019
The Member Election Subcommittee of the SLTC is seeking nominations for new SLTC Members for a 3-year term (2020-2022). Nominations should
be submitted by filling out the web form at https://forms.gle/sm9pStwFFK63zWem8. The nomination deadline is October 20th, 2019.
In a typical communication pipeline, images undergo a series of processing steps that can cause visual distortions before being viewed. Given a high quality reference image, a reference (R) image quality assessment (IQA) algorithm can be applied after compression or transmission. However, the assumption of a high quality reference image is often not fulfilled in practice, thus contributing to less accurate quality predictions when using stand-alone R IQA models.
In this paper, we present a novel Bayesian classification framework of the matrix variate Bingham distributions with the inclusion of its normalizing constant and develop a consistent general parametric modeling framework based on the Grassmann manifolds. To calculate the normalizing constants of the Bingham model, this paper extends the method of saddle-point approximation (SPA) to a new setting.
To promote the applications of semantic segmentation, quality evaluation is important to assess different algorithms and guide their development and optimization. In this paper, we establish a subjective semantic segmentation quality assessment database based on the stimulus-comparison method. Given that the database reflects the relative quality of semantic segmentation result pairs...