ReVerb Challenge (REverberant Voice Enhancement and Recognition Benchmark)

REVERB（REverberant Voice Enhancement and Recognition Benchmark）挑战是评估自动语音识别技术的基准。挑战假设在混响会议室中使用 1 通道、2 通道或 8 通道麦克风阵列捕获单个静止的远方说话者所说的话语。它具有真实记录和模拟数据。挑战包括混响环境中的语音增强和自动语音识别任务。语音增强挑战任务包括使用单通道/多通道语音增强技术增强嘈杂的混响语音，并根据客观和主观评估指标评估增强数据。自动语音识别挑战任务包括提高相同混响语音的识别精度。背景噪声大多是静止的，信噪比适中。

REVERB (REverberant Voice Enhancement and Recognition Benchmark) challenge is a benchmark for evaluating automatic speech recognition (ASR) technologies. The challenge assumes that utterances from a single stationary far-field speaker are captured using 1-channel, 2-channel, or 8-channel microphone arrays in a reverberant meeting room. It includes both real-recorded and simulated data. The challenge encompasses two tasks: speech enhancement and automatic speech recognition in reverberant environments. The speech enhancement challenge task involves enhancing noisy reverberant speech via single-channel or multi-channel speech enhancement techniques, and evaluating the enhanced data using both objective and subjective evaluation metrics. The automatic speech recognition challenge task aims to improve the recognition accuracy of the same reverberant speech. The background noise is mostly stationary, with a moderate signal-to-noise ratio (SNR).

搜集汇总

背景与挑战

背景概述

ReVerb Challenge是一个专注于混响环境下语音增强和自动语音识别评估的基准数据集。它使用1通道、2通道或8通道麦克风阵列捕获混响会议室中的语音，包含真实和模拟数据，任务包括增强嘈杂混响语音并评估其质量，以及提高语音识别精度，背景噪声以静止为主且信噪比适中。