#jupyter_notebook #asr #asr_benchmark #colab #english #enterprise_grade_stt #german #pretrained_models #pytorch #silero_models #spanish #speech_recognition #speech_to_text #stt #stt_benchmark

https://github.com/snakers4/silero-models

#python #callcenter #conformer #ctc_decode #deepspeech #fastspeech2 #language_model #mandarin_language #ngram #parallel_wavegan #punctuation_restoration #speech_alignment #speech_recognition #speech_to_text #speech_translation #streaming_asr #text_frontend #text_to_speech #transformer

https://github.com/PaddlePaddle/PaddleSpeech

#cplusplus #android #asr #deep_learning #deep_neural_networks #deepspeech #google_speech_to_text #ios #kaldi #offline #privacy #python #raspberry_pi #speaker_identification #speaker_verification #speech_recognition #speech_to_text #speech_to_text_android #stt #voice_recognition #vosk

https://github.com/alphacep/vosk-api

#typescript #alchemy #chartjs #ethereum #hardhat #ipfs #moralis #speech_recognition #xlsx

https://github.com/J0SAL/Decentralized-Expense-Tracker

#python #conformer #modelscope #paraformer #punctuation #pytorch #rnnt #speaker_diarization #speech_recognition #vad

https://github.com/alibaba-damo-academy/FunASR

#python #automatic_speech_recognition #docker #openai_whisper #speech_recognition #speech_to_text

https://github.com/ahmetoner/whisper-asr-webservice

#swift #inference #ios #macos #pretrained_models #speech_recognition #swift #transformers #visionos #watchos #whisper

WhisperKit is a tool that helps your Apple devices recognize speech from audio files or live recordings using OpenAI's Whisper model. It works locally on your device, which means it doesn't need internet connection once set up. To use it, you can add WhisperKit to your Swift project easily through the Swift Package Manager or install a command-line version using Homebrew. This tool is beneficial because it allows you to transcribe audio quickly and efficiently right on your device, making it useful for various applications like voice assistants or transcription services.

https://github.com/argmaxinc/WhisperKit

#python #bert #deep_learning #flax #hacktoberfest #jax #language_model #language_models #machine_learning #model_hub #natural_language_processing #nlp #nlp_library #pretrained_models #python #pytorch #pytorch_transformers #seq2seq #speech_recognition #tensorflow #transformer

The Hugging Face Transformers library provides thousands of pretrained models for various tasks like text, image, and audio processing. These models can be used for tasks such as text classification, image detection, speech recognition, and more. The library supports popular deep learning frameworks like JAX, PyTorch, and TensorFlow, making it easy to switch between them.

The benefit to the user is that you can quickly download and use these pretrained models with just a few lines of code, saving time and computational resources. You can also fine-tune these models on your own datasets and share them with the community. Additionally, the library offers a simple `pipeline` API for immediate use on different inputs, making it user-friendly for both researchers and practitioners. This helps in reducing compute costs and carbon footprint while enabling high-performance results across various machine learning tasks.

https://github.com/huggingface/transformers

#jupyter_notebook #computer_vision #deep_learning #drug_discovery #forecasting #large_language_models #mxnet #nlp #paddlepaddle #pytorch #recommender_systems #speech_recognition #speech_synthesis #tensorflow #tensorflow2 #translation

This repository provides top-quality deep learning examples that are easy to train and deploy on NVIDIA GPUs. It includes a wide range of models for computer vision, natural language processing, recommender systems, speech to text, and more. These examples are updated monthly and come in Docker containers with the latest NVIDIA software, ensuring the best performance. The models support multiple GPUs and nodes, and some are optimized for Tensor Cores, which can significantly speed up training. This makes it easier for users to achieve high accuracy and performance in their deep learning projects.

https://github.com/NVIDIA/DeepLearningExamples

#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