Search Results for "audio waveform"
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Showing 64 open source projects for "audio waveform"
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MLX-Audio
A text-to-speech, speech-to-text and speech-to-speech library
...The project provides a straightforward CLI (mlx_audio.tts.generate) as well as a Python API for programmatic generation of audio, including parameters for voice choice, speed, language hints, output format, and sample rate. It includes examples such as audiobook generation to demonstrate long-form synthesis and joined audio segments. On top of that, MLX-Audio offers a modern web interface powered by FastAPI, with real-time waveform and 3D visualizations, file upload, and audio management. -
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wavesurfer.js
Navigable waveform built on Web Audio and Canvas
...You can also try wavesurfer.swf which is a Flash-based fallback. The audio will start playing as you press play. A thin line will be displayed until the whole audio file is downloaded and decoded to draw the waveform. Web Audio needs the whole file to decode it in the browser. You can however load pre-decoded waveform data to draw the waveform immediately. wavesurfer.js runs on modern browsers supporting Web Audio, including Firefox, Chrome, Safari (desktop and mobile) and Opera. -
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FDWaveformView
Reads an audio file and displays the waveform
FDWaveformView is an easy way to display an audio waveform in your app. It is a nice visualization to show a playing audio file or to select a position in a file. To use it, add an FDWaveformView using Interface Builder or programmatically and then just load your audio as per this example. -
4
Color to Waveform
Convert colors to synth presets
The purpose of the program is to convert a color to a waveform you can use as a synthesizer oscillator inside a DAW such as FL Studio from Image Line. Many synths are provided with an option to load your own waveform, to replace the basic saw, square and sine waveforms commonly used to create synth sounds. The waveform generated by the program will correspond to the subliminal synesthetic sensation of the selected color. You can create your own synth presets to use in a track using color as a base. -
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Step-Audio-EditX
LLM-based Reinforcement Learning audio edit model
Step-Audio-EditX is an open-source, 3 billion-parameter audio model from StepFun AI designed to make expressive and precise editing of speech and audio as easy as text editing. Rather than treating audio editing as low-level waveform manipulation, this model converts speech into a sequence of discrete “audio tokens” (via a dual-codebook tokenizer) — combining a linguistic token stream and a semantic (prosody/emotion/style) token stream — thereby abstracting audio editing into high-level token operations. ... -
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pyAudioAnalysis
Python Audio Analysis Library: Feature Extraction, Classification
pyAudioAnalysis is an open-source Python library designed for audio signal analysis, machine learning, and music information retrieval tasks. The project provides a collection of tools that allow developers to extract meaningful features from audio files and use those features for classification, segmentation, and analysis. The library supports multiple audio processing workflows, including feature extraction from raw audio signals, training of machine learning models, and automatic audio... -
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AudioKit
Swift audio synthesis, processing, & analysis platform
AudioKit is an entire audio development ecosystem of code repositories, packages, libraries, algorithms, applications, playgorunds, tests, and scripts, built and used by a community of audio programmers, app developers, engineers, researchers, scientists, musicians, gamers, and people new to programming. An important goal for AudioKit is to allow it to grow and be maintainable by a handful of volunteers. For this reason we have extensive tests that are run whenever changes are made to any... -
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TorchAudio
Data manipulation and transformation for audio signal processing
The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. The benefits of PyTorch can be seen in torchaudio through having all the computations be through PyTorch... -
9
WavTokenizer
SOTA discrete acoustic codec models with 40/75 tokens per second
...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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II ElevenLabs UI
Component library and custom registry built on top of shadcn/ui
ElevenLabs UI is an open-source component library designed to accelerate the development of multimodal AI applications, particularly those involving voice agents and audio-based interactions. Built on top of modern frontend tooling such as React, Tailwind CSS, and shadcn/ui, it provides a collection of pre-built, customizable components that developers can easily integrate into their applications. The library includes specialized UI elements such as audio players, waveform visualizers, conversational interfaces, and interactive voice components, all tailored for building agent-driven experiences. ... -
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Subtitle-Workshop-Classic-v6.3.4
Subtitle Editor derived from 6.0c, but with VLC and Hunspell checker
Audio waveform, VLC Video Renderer, UTF8 coding, Audio stream detection and Selection, Resizeable screens, Hunspell spellcheck, Easy shortcut editing, user profiles and more than 70 filetypes supported. -
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WhisperSpeech
An Open Source text-to-speech system built by inverting Whisper
WhisperSpeech is an open-source text-to-speech system created by “inverting” OpenAI’s Whisper, reusing its strengths as a semantic audio model to generate speech instead of only transcribing it. The project aims to be for speech what Stable Diffusion is for images: powerful, hackable, and safe for commercial use, with code under Apache-2.0/MIT and models trained only on properly licensed data. Its architecture follows a token-based, multi-stage pipeline inspired by AudioLM and SPEAR-TTS: Whisper is used to produce semantic tokens, EnCodec compresses the waveform into acoustic tokens, and Vocos reconstructs high-fidelity audio from those tokens. ... -
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DesktopWebRadio Win Forms .Net 8: Loads radio stations from the InternetRadio.csv file which must be placed in the main directory. Modifies the color theme based on MaterialSkin options. Displays audio waveform animations. Displays song metadata: 'Station', 'Artist', 'Song Title', when available. Displays album covers when available on Discogs or Last.fm; clicking on the control displays an enlarged image of the cover. v1.1.0 .Net Framework 4.8
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Text to Waveform
Create synth presets from words
Convert words to waveforms you can load into a synthesizer oscillator to create synth presets. Have fun turning your name, your friends' names, your city name, your pet's name, your team's name into synth presets you can use to produce a track. -
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Kytner Video Cutter Studio
Easy, free Windows video editor with LUT support, cuts, and Splits+FX.
... 🚀 Key Features Advanced Cutting: Frame-accurate trimming with a dedicated Marker System. Cinematic Grading: Adjust saturation/contrast or apply custom .cube LUTs. Visual Effects: High-quality blur and intuitive Drag & Drop text overlays. Audio-Visual Sync: High-fidelity waveform display for perfect timing. Seamless Handling: Lossless Video Splitter and Merger. Safety: Full Undo/Redo support for every action. Global: Localized in EN, DE, ES, FR, JP, and RU. 💻 Requirements OS: Windows 10 20H2 (64-bit)+ | Framework: .NET 4.8.1 RAM: 8GB (16GB rec.) | Space: 1000MB Note: FFmpeg requested on first launch. -
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LoopAuditioneer
Software for loop and cue handling in .wav files.
Since 2024-02-28 development of LoopAuditioneer has moved to GitHub. Please go to https://github.com/GrandOrgue/LoopAuditioneer for recent updates and releases. -
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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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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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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... -
20
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. -
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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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EnCodec
State-of-the-art deep learning based audio codec
Encodec is a neural audio codec developed by Meta for high-fidelity, low-bitrate audio compression using end-to-end deep learning. 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. ... -
23
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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VoiceFixer
General Speech Restoration
VoiceFixer is a machine-learning framework for “speech restoration”: given a degraded or distorted audio recording — with noise, clipping, low sampling rate, reverberation, or other artifacts — it attempts to recover high-fidelity, clean speech. 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. ... -
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Denoiser
Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)
Denoiser is a real-time speech enhancement model operating directly on raw waveforms, designed to clean noisy audio while running efficiently on CPU. 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.
