Search Results for "vector quantization"

AGC (Audiogen Codec) is a convolutional autoencoder based on the DAC architecture, which holds SOTA. We found that training with EMA and adding a perceptual loss term with CLAP features improved performance. These codecs, being low compression, outperform Meta's EnCodec and DAC on general audio as validated from internal blind ELO games. We trained (relatively) very low compression codecs in the pursuit of solving a core issue regarding general music and audio generation, low acoustic...

Implementation of NÜWA, state of the art attention network for text-to-video synthesis, in Pytorch. It also contains an extension into video and audio generation, using a dual decoder approach. It seems as though a diffusion-based method has taken the new throne for SOTA. However, I will continue on with NUWA, extending it to use multi-headed codes + hierarchical causal transformer. I think that direction is untapped for improving on this line of work. In the paper, they also present a way...

Implementation of RQ Transformer, which proposes a more efficient way of training multi-dimensional sequences autoregressively. This repository will only contain the transformer for now. You can use this vector quantization library for the residual VQ. This type of axial autoregressive transformer should be compatible with memcodes, proposed in NWT. It would likely also work well with multi-headed VQ. I also think there is something deeper going on, and have generalized this to any number...

SPTK is a suite of speech signal processing tools for UNIX environments, e.g., LPC analysis, PARCOR analysis, LSP analysis, PARCOR synthesis filter, LSP synthesis filter, vector quantization techniques, and other extended versions of them.

Implementation of the algorithm of the paper: "Fractal image compression based on Delaunay triangulation and vector quantization" It is a Fractal compression algorithm, based on relationships between regions of the image (in this case triangles), rather than in explicitly the pixel values themselves. Video demo: https://frojasg1.com:8443/resource_counter/resourceCounter?operation=countAndForward&url=https%3A%2F%2Ffrojasg1.com%2Fdemos%2Faplicaciones%2FfractalCompressor...

Some of the usual problems for Learning vector quantization (LVQ) based methods are that one cannot optimally guess about the number of prototypes required for initialization for multimodal data structures i.e.these algorithms are very sensitive to initialization of prototypes and one has to pre define the optimal number of prototypes before running the algorithm. If a prototype, for some reasons, is ‘outside’ the cluster which it should represent and if there are points of a different...

drvq is a C++ library implementation of dimensionality-recursive vector quantization, a fast vector quantization method in high-dimensional Euclidean spaces under arbitrary data distributions. It is an approximation of k-means that is practically constant in data size and applies to arbitrarily high dimensions but can only scale to a few thousands of centroids. As a by-product of training, a tree structure performs either exact or approximate quantization on trained centroids, the latter...

... - Vector quantization using the k-means algorithm - Uses the algorithm Forward - Uses the algorithm Backward - Uses the Viterbi algorithm - Uses the Baum-Welch algorithm for training - Has features import and export data Further information is on Gaita 2012.

libit provides easy to use yet efficient tools for C for signal processing, coding, or scientific code in general. It includes basic vector, matrix and function types, some common source and channel coding tools such as quantization, entropy coding, etc.