#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
https://github.com/PaddlePaddle/PaddleSpeech
GitHub
GitHub - PaddlePaddle/PaddleSpeech: Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with…
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 Translatio...
#python #asr #deeplearning #generative_ai #large_language_models #machine_translation #multimodal #neural_networks #speaker_diariazation #speaker_recognition #speech_synthesis #speech_translation #tts
NVIDIA NeMo is a powerful, easy-to-use platform for building, customizing, and deploying generative AI models like large language models (LLMs), vision language models, and speech AI. It lets you quickly train and fine-tune models using pre-built code and checkpoints, supports the latest model architectures, and works on cloud, data center, or edge environments. NeMo 2.0 is even more flexible and scalable, with Python-based configuration and modular design, making it simple to experiment and scale up. The main benefit is that you can create advanced AI applications faster, with less effort, and at lower cost, while getting high performance and easy deployment options[1][2][3].
https://github.com/NVIDIA/NeMo
NVIDIA NeMo is a powerful, easy-to-use platform for building, customizing, and deploying generative AI models like large language models (LLMs), vision language models, and speech AI. It lets you quickly train and fine-tune models using pre-built code and checkpoints, supports the latest model architectures, and works on cloud, data center, or edge environments. NeMo 2.0 is even more flexible and scalable, with Python-based configuration and modular design, making it simple to experiment and scale up. The main benefit is that you can create advanced AI applications faster, with less effort, and at lower cost, while getting high performance and easy deployment options[1][2][3].
https://github.com/NVIDIA/NeMo
GitHub
GitHub - NVIDIA-NeMo/Speech: A scalable generative AI framework built for researchers and developers working on Large Language…
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) - NVIDIA-NeMo/S...
#python #ai #assistant #language_model #machine_learning #python #speech #speech_synthesis #speech_to_text #speech_translation
I can help you build a fast, modular voice agent that turns speech into text, sends it to a language model, then speaks the answer back. It works with open-source or hosted models, can run fully local on your own hardware, and supports live transcription and low-latency conversation, so you get a flexible voice app that you can customize for speed, privacy, and different devices.
https://github.com/huggingface/speech-to-speech
I can help you build a fast, modular voice agent that turns speech into text, sends it to a language model, then speaks the answer back. It works with open-source or hosted models, can run fully local on your own hardware, and supports live transcription and low-latency conversation, so you get a flexible voice app that you can customize for speed, privacy, and different devices.
https://github.com/huggingface/speech-to-speech
GitHub
GitHub - huggingface/speech-to-speech: Build local voice agents with open-source models
Build local voice agents with open-source models. Contribute to huggingface/speech-to-speech development by creating an account on GitHub.
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