End-to-end Speech Benchmark (ESB)

ESB是一个用于评估多领域端到端语音识别系统的基准数据集，由Hugging Face创建。该数据集包含多个语音数据集，覆盖不同的音频和文本分布，旨在推动多领域语音识别系统的研究。ESB数据集的特点是要求系统使用相同的数据预处理和后处理算法，不依赖于预先知道音频和文本数据分布。数据集的应用领域广泛，包括语音识别、语音转写等，旨在解决不同领域和条件下的语音识别问题。

ESB is a benchmark dataset for evaluating multi-domain end-to-end speech recognition systems, developed by Hugging Face. This dataset comprises multiple speech corpora, covering diverse audio and text distributions, with the goal of advancing research on multi-domain speech recognition systems. A distinctive feature of the ESB dataset is that it requires systems to use uniform data preprocessing and postprocessing algorithms, without relying on prior knowledge of the audio and text data distributions. The dataset has broad application scenarios, including speech recognition, speech transcription and other related tasks, and aims to address speech recognition challenges across various domains and conditions.

搜集汇总

背景与挑战

背景概述

ESB是一个由Hugging Face创建的基准数据集，用于评估多领域端到端语音识别系统。它包含多个语音数据集，覆盖不同音频和文本分布，要求系统使用统一的数据处理算法，不依赖预先数据分布知识，旨在推动语音识别研究并解决多领域问题。