#LibriSpeech

The repository provides a wide array of audio datasets, such as speech, music, and sound effects, that are crucial for training AI models and advancing AI-generated content. Supporting speech recognition, TTS systems, and research in emotion and language translation, these datasets accommodate various languages and demographics, suitable for both academic and commercial applications. Discover resources from multi-speaker corpora to diverse multilingual speech translation datasets, designed to promote innovation in audio AI technologies.

Deep Speaker is an end-to-end system developed using Tensorflow/Keras, facilitating tasks like speaker identification by mapping utterances through cosine similarity. It provides unofficial implementation and pretrained models supporting Tensorflow versions from 2.3 to 2.6, suggesting data preprocessing for noise reduction to optimize results.

Explore a diverse collection of speech datasets in multiple languages, including Chinese, English, and Japanese, designed for speech recognition, synthesis, and speaker diarization. This collection supports various applications, such as speech commands and ASR system evaluation, facilitating advancements in speech technology. Notable datasets like Common Voice and LibriSpeech play a crucial role in enhancing machine learning models. This resource is invaluable for researchers seeking comprehensive audio data for developing speech-related solutions across different linguistic contexts.