vakyansh-models
data-acquisition-pipeline
vakyansh-models | data-acquisition-pipeline | |
---|---|---|
2 | 1 | |
267 | 16 | |
0.0% | - | |
0.0 | 2.7 | |
over 1 year ago | about 3 years ago | |
Python | ||
MIT License | MIT License |
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vakyansh-models
data-acquisition-pipeline
-
GitHub - Open-Speech-EkStep/vakyansh-models: Open source speech to text models for Indic Languages
https://github.com/Open-Speech-EkStep/crowdsource-dataplatform https://github.com/Open-Speech-EkStep/data-acquisition-pipeline See https://open-speech-ekstep.github.io/
What are some alternatives?
STT - 🐸STT - The deep learning toolkit for Speech-to-Text. Training and deploying STT models has never been so easy.
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
NeMo - A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
flashlight - A C++ standalone library for machine learning
PaddleSpeech - Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.
common-voice - Common Voice is part of Mozilla's initiative to help teach machines how real people speak.
edgedict - Working online speech recognition based on RNN Transducer. ( Trained model release available in release )
TTS - :robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
DNS-Challenge - This repo contains the scripts, models, and required files for the Deep Noise Suppression (DNS) Challenge.
DeepSpeech - DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
crowdsource-dataplatform - This will hold the crowdsourcing platform to be used to store voice data from various speakers which will act as input dataset for speech-to-text pipeline