kaldi-asr/kaldi is the official location of the Kaldi project.

For HOT news about Kaldi see the project site. Info about the project, description of techniques, tutorial for C++ coding. Doxygen reference of the C++ code. User list kaldi-help Developer list kaldi-developers: 

SpeechBrain is an open-source and all-in-one conversational AI toolkit based on PyTorch. The goal is to create a single, flexible, and user-friendly toolkit that can be used to easily develop state-of-the-art speech technologies, including systems for speech recognition, speaker recognition, speech enhancement, speech separation, language identification, multi-microphone signal processing, and many others. Various pretrained models nicely integrated with  (HuggingFace) in our official organization account. These models are coupled with easy-inference interfaces that facilitate their use. To help everyone replicate our results, we also provide all the experimental results and folders (including logs, training curves, etc.) in a shared Google Drive folder. The Brain class, a fully-customizable tool for managing training and evaluation loops over data. The annoying details of training loops are handled for you while retaining complete flexibility to override any part of the process when needed. A YAML-based hyperparameter file that specifies all the hyperparameters, from individual numbers (e.g., learning rate) to complete objects (e.g., custom models). This elegant solution dramatically simplifies the training script. Multi-GPU training and inference with PyTorch Data-Parallel or Distributed Data-Parallel. Mixed-precision for faster training. A transparent and entirely customizable data input and output pipeline. SpeechBrain follows the PyTorch data loading style and enables users to customize the I/O pipelines (e.g., adding on-the-fly downsampling, BPE tokenization, sorting, threshold ...). On-the-fly dynamic batching Efficient reading of large datasets from a shared Network File System (NFS) via WebDataset. Interface with HuggingFace for popular models such as wav2vec2 and Hubert. Interface with Orion for hyperparameter tuning. 

SoundFile is an audio library based on libsndfile, CFFI, and NumPy

A python package to analyze and compare voices with deep learning

Resemblyzer allows you to derive a high-level representation of a voice through a deep learning model (referred to as the voice encoder). Given an audio file of speech, it creates a summary vector of 256 values (an embedding, often shortened to "embed" in this repo) that summarizes the characteristics of the voice spoken. N.B.: this repo holds 100mb of audio data for demonstration purpose. To get the package alone, run pip install resemblyzer (python 3.5+ is required). 

Speech Recognition

Group Name 1

kaldiby kaldi-asr

kaldiby kaldi-asr

speechbrainby speechbrain

speechbrainby speechbrain

python-soundfileby bastibe

python-soundfileby bastibe

Group Name 2

Resemblyzerby resemble-ai

Resemblyzerby resemble-ai