Search Results for "waveform" - Page 2
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Showing 81 open source projects for "waveform"
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DSpice
DSpice: Design and Simulation of Circuits using Spice
...Schematic Capture: Drawing and designing circuits using an intuitive CAD-style schematic editor. . Circuit Simulation: Executing simulations (OP/Tran) seamlessly using ngspice. . Waveform Visualization: Analyzing and presenting simulation results through a dedicated waveform viewer and Prob. . Licensed under: DSPICE is free to use "MIT"; . Open source; -
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...However, it also offers extra functionality via applications and utilities developed by others. Electronic Design Automation (EDA) tool suites are used to provide schematic capture and editing, and schematic to netlist conversion. Waveform data viewers are used to display simulation results and PDF viewers to display user manuals.
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...At the time of writing the publication, limr builded upon gateware version 2.17 from June 2018, which was used with API version 18.04.19. Feb2022: LimeSDR USB gateware/API updates, including a new optional gateware fork that allows to playback a waveform directly from LimeSDR memory, which is very useful for setting up CW experiments. Jan2024: LimeSDR Mini 2.0 gateware added Do not hesitate to ask in case of installation problems
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MD Synth DAW
Write music for the Sega Mega Drive
Write music for the Sega Mega Drive Or just make music with the same limits the console had. The YM2612 and the SN76489 synthesizers are your instruments. -
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garysfm
An advanced file manager with qss themes and iso and folder previews
garysfm which stands for Gary's File Manager is a file manager with some advanced features. Those features include bulk renaming and folder image previews. I has rather advanced search functions, tab browsing with persistence between launches. It remembers your folder sorting and view options in icon view. It also remembers your active tabs between sessions. It has progress dialog while doing large operations like copying large files, and folders with many files. python version works on... -
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vmio
A VMIO is a software oscilloscope.
...The main purposes are to display repetitive or single waveforms on the screen that would otherwise occur too briefly to be perceived by the human eye. The displayed waveform can then be analyzed for properties such as bit value, frequency, rise timestamp, time interval and others. Calculation of these values require analyzing the waveform against the scales built into the screen of the VMIO. This powerful utility is a handy tool for hardware engineers, BIOS engineers, driver developers, QA engineers, performance test engineers, diagnostic engineer, etc. it can be used in the sciences, medicine, engineering, automotive and the telecommunications industry. ... -
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Parallel WaveGAN
Unofficial Parallel WaveGAN
Parallel WaveGAN is an unofficial PyTorch implementation of several state-of-the-art non-autoregressive neural vocoders, centered on Parallel WaveGAN but also including MelGAN, Multiband-MelGAN, HiFi-GAN, and StyleMelGAN. Its main goal is to provide a real-time neural vocoder that can turn mel spectrograms into high-quality speech audio efficiently. The repository is designed to work hand-in-hand with ESPnet-TTS and NVIDIA Tacotron2-style front ends, so you can build complete TTS or singing... -
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Quick Subtitles
HTML5 Based Subtitle Creation Tool
Quick Subtitles in an HTML5 based solution for rapid creation and syncing of subtitles while playing your video. It is designed around the concept that you should minimize the need to take your hands off the keyboard while performing data entry. -
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Demucs
Code for the paper Hybrid Spectrogram and Waveform Source Separation
Demucs (Deep Extractor for Music Sources) is a deep-learning framework for music source separation—extracting individual instrument or vocal tracks from a mixed audio file. The system is based on a U-Net-like convolutional architecture combined with recurrent and transformer elements to capture both short-term and long-term temporal structure. It processes raw waveforms directly rather than spectrograms, allowing for higher-quality reconstruction and fewer artifacts in separated tracks. The... -
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VALL-E
PyTorch implementation of VALL-E (Zero-Shot Text-To-Speech)
We introduce a language modeling approach for text to speech synthesis (TTS). Specifically, we train a neural codec language model (called VALL-E) using discrete codes derived from an off-the-shelf neural audio codec model, and regard TTS as a conditional language modeling task rather than continuous signal regression as in previous work. During the pre-training stage, we scale up the TTS training data to 60K hours of English speech which is hundreds of times larger than existing systems.... -
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audio-diffusion-pytorch
Audio generation using diffusion models, in PyTorch
A fully featured audio diffusion library, for PyTorch. Includes models for unconditional audio generation, text-conditional audio generation, diffusion autoencoding, upsampling, and vocoding. The provided models are waveform-based, however, the U-Net (built using a-unet), DiffusionModel, diffusion method, and diffusion samplers are both generic to any dimension and highly customizable to work on other formats. Note: no pre-trained models are provided here, this library is meant for research purposes. -
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WaveformSeekBar
Android Waveform SeekBar library
Android Waveform SeekBar library. -
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EnCodec
State-of-the-art deep learning based audio codec
...Unlike traditional codecs (like MP3 or Opus), Encodec uses a learned quantizer and decoder to reconstruct complex waveforms with remarkable accuracy at bitrates as low as 1.5 kbps. It employs a convolutional encoder–decoder architecture trained with perceptual loss functions that optimize for human auditory quality rather than raw waveform distance. The model can operate in real time and supports variable bandwidths, bitrates, and multi-band audio. Encodec has applications in speech and music compression, generative modeling, and efficient data transmission for communication systems. The repository includes pretrained checkpoints, PyTorch inference code, and examples for integrating Encodec as a module in downstream generative or streaming systems. -
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DiffSinger
Singing Voice Synthesis via Shallow Diffusion Mechanism
DiffSinger is an open-source PyTorch implementation of a diffusion-based acoustic model for singing-voice synthesis (SVS) and also text-to-speech (TTS) in a related variant. The core idea is to view generation of a sung voice (mel-spectrogram) as a diffusion process: starting from noise, the model iteratively “denoises” while being conditioned on a music score (lyrics, pitch, musical timing). This avoids some of the typical problems of prior SVS models — like over-smoothing or unstable GAN... -
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WaveRNN
WaveRNN Vocoder + TTS
WaveRNN is a PyTorch implementation of DeepMind’s WaveRNN vocoder, bundled with a Tacotron-style TTS front end to form a complete text-to-speech stack. As a vocoder, WaveRNN models raw audio with a compact recurrent neural network that can generate high-quality waveforms more efficiently than many traditional autoregressive models. The repository includes scripts and code for preprocessing datasets such as LJSpeech, training Tacotron to produce mel spectrograms, training WaveRNN on those... -
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kbd-audio
Acoustic keyboard eavesdropping
kbd-audio is a collection of command-line and graphical tools for capturing, visualizing, and analyzing keyboard audio. Its Keytap utilities explore whether pressed keys can be identified from sounds recorded through a nearby microphone. The original Keytap uses training recordings, while Keytap2 relies on English letter and n-gram frequency statistics. Keytap3 improves the algorithms and automates the recovery of unknown typed text without manual intervention. Additional tools record audio,... -
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VoiceFixer
General Speech Restoration
...The architecture works in two stages: first an analysis stage that tries to extract “clean” intermediate features from the noisy audio (e.g. removing noise, denoising, dereverberation, upsampling), and then a neural vocoder-based synthesis stage that reconstructs a high-quality waveform from those features. Unlike many single-purpose noise reduction tools, VoiceFixer targets a “general speech restoration” problem (GSR), capable of handling multiple types of distortions at once, which makes it suitable for old recordings, phone-call audio, amateur voice recordings, or archival media. Evaluations show that VoiceFixer significantly improves both objective and subjective audio quality compared to baseline speech-enhancement methods. -
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TensorFlowTTS
Real-Time State-of-the-art Speech Synthesis for Tensorflow 2
TensorFlowTTS is a state-of-the-art, open-source speech synthesis library built on TensorFlow 2. It offers a variety of architectures for text-to-speech, including classic and modern models such as Tacotron‑2, FastSpeech / FastSpeech2, and neural vocoders like MelGAN and Multiband‑MelGAN. Because it’s based on TensorFlow 2, it can leverage optimizations such as fake-quantization aware training and pruning — which allow models to run faster than real time and to be deployable on mobile or... -
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VITS
Conditional Variational Autoencoder with Adversarial Learning
VITS is a foundational research implementation of “VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech,” a well-known neural TTS architecture. Unlike traditional two-stage systems that separately train an acoustic model and a vocoder, VITS trains an end-to-end model that maps text directly to waveform using a conditional variational autoencoder combined with normalizing flows and adversarial training. This architecture enables parallel generation (fast inference) while achieving speech quality that rivals or surpasses many two-stage systems. The repository provides training and inference pipelines for common datasets such as LJ Speech (single-speaker) and VCTK (multi-speaker), including filelists, configs, and preprocessing scripts. ... -
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Denoiser
Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)
...It uses a causal encoder-decoder architecture with skip connections, optimized with losses defined both in the time domain and frequency domain to better suppress noise while preserving speech. Unlike models that operate on spectrograms alone, this design enables lower latency and coherent waveform output. The implementation includes data augmentation techniques applied to the raw waveforms (e.g. noise mixing, reverberation) to improve model robustness and generalization to diverse noise types. The project supports both offline denoising (batch inference) and live audio processing (e.g. via loopback audio interfaces), making it practical for real-time use in calls or recording. ... -
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HiFi-GAN
Generative Adversarial Networks for Efficient and High Fidelity Speech
...It introduces a generator architecture tailored to model the periodic structure of speech and a set of discriminators that focus on different scales and periods of the waveform to better capture naturalness. The model targets a sweet spot between sample quality and generation speed, outperforming many previous GAN vocoders while being far faster than typical autoregressive models. In experiments on LJSpeech, HiFi-GAN was shown to achieve mean opinion scores close to human recordings while synthesizing 22.05 kHz audio up to ~168× faster than real time on an NVIDIA V100 GPU. ... -
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Timewave Synthesizer
A binary waveform synthesizer based on Timewave Zero
A binary waveform synthesizer derived from and based upon Timewave Zero theory by Terence McKenna. His theory proposes that the structure of time is a complex wave with a scalar potential, and the King Wen sequence of the I Ching is the 64 hexagram code from which the waveform of time is derived; that the King Wen sequence maps the linear progression of the human states of mind, which ultimately substantiates this waveform. -
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WaveDrom
Digital timing diagram rendering engine
...WaveDrom draws your Timing Diagram or Waveform from a simple textual description. It comes with description language, a rendering engine and an editor. WaveDrom editor works in the browser or can be installed on your system. -
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GLava
GLava - OpenGL audio spectrum visualizer
GLava is a real-time OpenGL audio spectrum visualizer for Linux desktops that renders directly onto your desktop background. Designed for users who enjoy live audio visualizations integrated with their environment, it supports shader-based effects and customization for creating stunning reactive visuals. GLava works with PulseAudio and ALSA and can be embedded seamlessly with tiling window managers or traditional desktop setups. Its configuration is flexible, allowing the community to design... -
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Tacotron-2
DeepMind's Tacotron-2 Tensorflow implementation
...The repository is structured as a full training pipeline: dataset preparation, preprocessing into spectrograms, Tacotron training, WaveNet (or Griffin-Lim) vocoder training, and final waveform synthesis. It includes directory layouts and logging directories for multiple datasets such as LJSpeech and M-AILABS en_US/en_UK, making it easier to adapt to new English corpora. Separate log trees track mel-spectrograms, attention plots, evaluation audio, and vocoder outputs, so you can inspect how alignment and audio quality evolve over time.
