#rust #audio_processing #digital_signal_processing #dsp #fft #fourier_transform

https://github.com/calebzulawski/fourier

#python #artificial_intelligence #audio_processing #deep_learning #deeplearning #embeddings #encodings #image2vec #machine_learning #neural_network #pytorch #tensorflow #tfhub #transformers #vector #vector_similarity #video_processing #word2vec

https://github.com/vector-ai/vectorhub

#c_lang #audio_applications #libre #floss #audacity #audio_processing

https://github.com/tenacityteam/tenacity

#cplusplus #audio_processing #audio_production #audio_research #audio_unit #juce #pybind11 #python #tensorflow #vst3 #vst3_host

https://github.com/spotify/pedalboard

#python #action_recognition #anomaly_detection #audio_processing #background_removal #crowd_counting #deep_learning #face_detection #face_recognition #fashion_ai #gan #hand_detection #image_classification #image_segmentation #machine_learning #neural_network #object_detection #object_recognition #object_tracking #pose_estimation

https://github.com/axinc-ai/ailia-models

#cplusplus #android #audio_processing #c_plus_plus #calculator #computer_vision #deep_learning #framework #graph_based #graph_framework #inference #machine_learning #mediapipe #mobile_development #perception #pipeline_framework #stream_processing #video_processing

MediaPipe is a tool that helps you add smart machine learning features to your apps and devices. It works on mobile, web, desktop, and other devices. You can use pre-made solutions for tasks like vision, text, and audio processing, or customize the models to fit your needs. MediaPipe also offers tools like Model Maker and Studio to help you create and test your solutions easily. This makes it easier to delight your customers with innovative features without needing deep machine learning expertise.

https://github.com/google-ai-edge/mediapipe

#python #asr #audio #audio_processing #deep_learning #huggingface #language_model #pytorch #speaker_diarization #speaker_recognition #speaker_verification #speech_enhancement #speech_processing #speech_recognition #speech_separation #speech_to_text #speech_toolkit #speechrecognition #spoken_language_understanding #transformers #voice_recognition

SpeechBrain is an open-source toolkit that helps you quickly develop Conversational AI technologies, such as speech assistants, chatbots, and language models. It uses PyTorch and offers many pre-trained models and tutorials to make it easy to get started. You can train models for various tasks like speech recognition, speaker recognition, and text processing with just a few lines of code. SpeechBrain also supports GPU training, dynamic batching, and integration with HuggingFace models, making it powerful and efficient. This toolkit is beneficial because it simplifies the development process, provides extensive documentation and tutorials, and is highly customizable, making it ideal for research, prototyping, and educational purposes.

https://github.com/speechbrain/speechbrain

#python #apple_silicon #audio_processing #mlx #multimodal #speech_recognition #speech_synthesis #speech_to_text #text_to_speech #transformers

MLX-Audio is a powerful tool for converting text into speech and speech into new audio. It works well on Apple Silicon devices, like M-series chips, making it fast and efficient. You can choose from different languages and voices, and even adjust how fast the speech is. It also includes a web interface where you can see audio in 3D and play your own files. This tool is helpful for making audiobooks, interactive media, and personal projects because it's easy to use and provides high-quality audio quickly.

https://github.com/Blaizzy/mlx-audio