Search Results for "vector quantization"
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Showing 13 open source projects for "vector quantization"
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Audiogen Codec
48khz stereo neural audio codec for general audio
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... -
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WavTokenizer
SOTA discrete acoustic codec models with 40/75 tokens per second
...The model uses a single-quantizer design together with temporal compression to achieve extreme compression without sacrificing reconstruction fidelity. Its architecture incorporates a broader vector-quantization space, extended contextual windows, and improved attention networks, combined with multi-scale discriminators and inverse Fourier transform blocks to enhance waveform reconstruction. Extensive experiments show that WavTokenizer matches or surpasses previous neural codecs across speech, music, and general audio on both objective metrics and subjective listening tests. -
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FractalImageCompression
Java Fractal Image Compression based on Delaunay triangulation
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%2Ffractal_image_compression_v1.0_demo.mp4%3Forigin%3Dsourceforge&origin=web -
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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.
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NÜWA - Pytorch
Implementation of NÜWA, attention network for text to video synthesis
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... -
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RQ-Transformer
Implementation of RQ Transformer, autoregressive image generation
...For autoregressive (AR) modeling of high-resolution images, vector quantization (VQ) represents an image as a sequence of discrete codes. A short sequence length is important for an AR model to reduce its computational costs to consider long-range interactions of codes. However, we postulate that previous VQ cannot shorten the code sequence and generate high-fidelity images together in terms of the rate-distortion trade-off. -
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DGRLVQ
Dynamic Generalized Relevance Learning Vector Quantization
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 categories in between, then the other points act as a barrier and the prototype will not find its optimum position during training. ... -
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drvq
dimensionality-recursive vector quantization
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 being not very precise but extremely fast. ... -
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JClassifier
Java data mining library and application
Java data mining library for multi-class one nearest neighbor classification and vector quantization by optimized dimension-wise hierarchical clustering to reduce data. The application can process LibSVM files. -
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SRM2 Sound Recognizer Mobile 2
A Sound Recognition Framework developed to J2ME plataform
The SRM Framework 2 was developed for the J2ME platform supporting sound recognition dependent and speaker-independent, through the recognition techniques DTW (Dynamic Time Warping) and HMM (Hidden Markov Models), in addition to providing support to the import and export of data any stage of recognition enabling the use of external resources as well as the tool running steps on remote terminals. It has the following characteristics: - DTW - HMM (Discrete Models) - Suports Sound in PCM - 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. -
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This project implements the parallelized version of the LBG vector quantization algorithm on Cell Broadband Engine.
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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.
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The ClustLib project is intended to build several C++ libraries with basic functionalities for clustering in the context of data mining. The planned packages include access to mysql databases, scaleable vector quantization, multidimensional density estim
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